Jobs

We’re building a world-class machine learning platform at Sixt and looking for a Senior Data Scientist to help shape our real-time dynamic pricing systems across global markets.

You’ll join a collaborative team working at the intersection of ML, experimentation, and pricing strategy, building algorithms that respond to market signals in real time and impact millions of customers.

This is a career-building opportunity for someone passionate about applied machine learning, optimization, and solving complex business challenges with measurable impact.

🔧 What You’ll Do

• Design and implement ML models for dynamic pricing, including experimentation-driven and real-time approaches
• Apply (or learn) methods such as multi-armed bandits, Bayesian inference, and reinforcement learning
• Collaborate with engineers, product managers, and pricing analysts to deploy scalable ML systems into production
• Monitor and evaluate model performance through A/B testing and real-world feedback loops
• Communicate methodologies, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to building a robust pricing decision engine integrated into global customer-facing systems

✅ What You Bring

We’re looking for someone with hands-on ML experience and a drive to apply it in production:

• B.Tech/B.E. or Master’s Degree in Computer Science, Engineering, or a related discipline (must-have)
• 5+ years of experience in machine learning, data science, or ML engineering
• Proficiency in Python, with experience in ML libraries such as PyTorch, TensorFlow, or scikit-learn
• Practical experience deploying ML models into production, ideally with tools like FastAPI, Docker, or MLflow
• Solid understanding of model evaluation, A/B testing, or real-time model monitoring
• Fluent English communication and the ability to work effectively in an international, cross-functional team

🌱 Nice to Have (We’ll Help You Learn)

These are a plus, but we’re happy to support your learning here:

• Experience with multi-armed bandits, reinforcement learning, or Bayesian modeling
• Knowledge of dynamic pricing, revenue management, or real-time optimization
• Familiarity with cloud ML platforms (AWS/GCP/Azure) or MLOps tooling
• Experience with streaming data or feedback-based model architectures

🚀 Career Path

This role is built for growth — start as a Senior Data Scientist with real impact, and evolve into a Lead ML Architect or Optimization Strategist, driving intelligent pricing at scale for Sixt.

🎁 What We Offer

• Competitive salary (settled in EUR, via direct employment at Sixt TECH Ukraine)
• 25 calendar days of paid vacation
• Full medical insurance
• Educational & learning budget
• Gym membership + language learning support
• Flat hierarchies, flexible hours, and zero corporate nonsense
• A truly global product and a high-impact role

About us:
Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with the organization of the first Data Science UA conference, setting the foundation for our growth. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the role:
We seek an experienced AI/ML Team Leader to join our Client’s startup team. As the Technical Lead, you will start with individual technical contributions and later will take an engineering manager role for the hiring team. You will create cutting-edge end-to-end AI camera solutions, effectively engage with customers and partners to grasp their requirements and ensure project success, overseeing from inception to completion.

Requirements:
- Proven leadership experience with a track record of managing and developing technical teams;
- Excellent customer-facing skills to understand and address client needs effectively;
- Master's Degree in Computer Science or related field (PhD is a plus);
- Solid grasp of machine learning and deep learning principles;
- Strong experience in Computer Vision, including object detection, segmentation, tracking, keypoint/pose estimation;
- Proven R&D mindset: capable of formulating and validating hypotheses independently, exploring novel approaches, and diving deep into model failures;
- Proficiency in Python and deep learning frameworks;
- Practical experience with state-of-the-art models, including different versions of YOLO and Transformer-based architectures (e.g., ViT, DETR, SAM);
- Expertise in image and video processing using OpenCV;
- Experience in model training, evaluation, and optimization;
- Fluent written and verbal communication skills in English.

Would be a plus:
- Experience applying ML techniques to embedded or resource-constrained environments (e.g. edge devices, mobile platforms, microcontrollers);
- Ideally, you have led projects where ML models were optimized, deployed, or fine-tuned for embedded systems, ensuring high performance and low latency under hardware limitations.

We offer:
- Free English classes with a native speaker and external courses compensation;
- PE support by professional accountants;
- 40 days of PTO;
- Medical insurance;
- Team-building events, conferences, meetups, and other activities;
- There are many other benefits you’ll find out at the interview.

PwC is a network of over 370,000 employees in 149 countries focused on providing the highest quality services in the areas of audit, tax advisory, consulting and technology development.

What we offer:
- Official employment;
- Remote work opportunity;
- Annual performance and grade review;
- A Dream team of experienced colleagues and high-class specialists;
- Language courses (English & Polish languages);
- Soft skills development;
- Personal development plan and career coach;
- Corporate events and team-buildings.

Main responsibilities:

• Developing innovative solutions for our clients by leveraging cutting-edge data science, machine learning, and AI technologies;
• Developing intelligent assistants using the latest large language models (e.g., GPT-4, Falcon 2, LLAMA 3, Mixtral), employing Retrieval Augmented Generation techniques, and utilizing agent frameworks (e.g., Langraph, CrewAI);
• Utilizing AI expertise to recommend the most effective technical approaches and solution architectures for addressing business challenges;
• Leading data science project teams of 1-5 members, managing small to medium projects, and overseeing parts of larger engagements under senior supervision;
• Working closely with PwC industry experts, clients, and higher management while actively participating in the proposal-making process within your area of expertise;
• Communicating complex insights in a clear and actionable manner to non-technical colleagues and clients.

Requirements:

• 3+ years of relevant professional experience;
• Solid knowledge of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model life-cycle, AI architectures;
• Knowledge and experience in production grade code development in Python;
• Solid knowledge of SQL;
• Experience with LLMs and related concepts (e.g. RAG, vector DBs, AI agents);
• Understanding of cloud concepts and architectures, with hands-on experience in cloud services (GCP, AWS, Azure);
• Knowledge of CI/CD and DevOps practices;
• Experience with deploying code with Docker / Kubernetes;
• Strong interpersonal and communication skills — essential in day-to-day cooperation with clients and the team;
• Outstanding supervision and mentorship abilities;
• Graduate of Economics, Econometrics, Quantitative Methods, Computer Science, Math, Physics, Operational Research or related discipline;
• Excellent analytical and problem-solving skills, including the ability to independently disaggregate issues, identify root causes and recommend solutions to business problems;

• Proficiency in English, both written and spoken.

   

  Nice to have: 

• Familiarity with MLOps tools (e.g., Azure AI Studio, AzureML, Vertex.AI, SageMaker, MLFlow);
• Knowledge of an extra programming language (e.g. C#, Go, Java);
• Knowledge of Natural Language Processing techniques;
• Experience in banking, retail or consulting;
• Experience in leading project teams.

Why PwC?

We are not just numbers and reports. PwC is the impact you can create through your actions. Our team will help you achieve more, and we are ready to start this journey with you.

Ready for a challenge? Send your resume and join the team that is shaping the future!

We are looking for a Computer Vision Engineer with a background in classical computer vision techniques and hands-on implementation of low-level CV algorithms. 

The ideal candidate will have experience with Object tracking, Visual-Inertial Odometry (VIO) and sensor fusion. 

We consider engineers at Middle+ and Senior levels - tasks and responsibilities will be adjusted accordingly. 

Required Qualifications: 

• 4+ years of hands-on experience with classical computer vision
• Understanding of geometrical computer vision principles 
• Hands-on experience in implementing low-level CV algorithms
• Proficiency in C++ 
• Experience with Linux 
• Experience with Object tracking and detection tasks 
• Ability to quickly navigate through recent research and trends in computer vision. 
• Familiarity with neural networks and common CV frameworks/libraries (OpenCV, NumPy, PyTorch, ONNX, Eigen, etc.) 

Nice to Have: 

• Practical experience with SLAM and/or Visual-Inertial Odometry (VIO) 
• Experience with Python 
• Experience with sensor fusion. 

About us:
Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with the organization of the first Data Science UA conference, setting the foundation for our growth. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the role:
We seek an experienced AI/ML Team Leader to join our Client’s startup team. As the Technical Lead, you will start with individual technical contributions and later will take an engineering manager role for the hiring team. You will create cutting-edge end-to-end AI camera solutions, effectively engage with customers and partners to grasp their requirements and ensure project success, overseeing from inception to completion.

Requirements:
- Proven leadership experience with a track record of managing and developing technical teams;
- Excellent customer-facing skills to understand and address client needs effectively;
- Master's Degree in Computer Science or related field (PhD is a plus);
- Solid grasp of machine learning and deep learning principles;
- Strong experience in Computer Vision, including object detection, segmentation, tracking, keypoint/pose estimation;
- Proven R&D mindset: capable of formulating and validating hypotheses independently, exploring novel approaches, and diving deep into model failures;
- Proficiency in Python and deep learning frameworks;
- Practical experience with state-of-the-art models, including different versions of YOLO and Transformer-based architectures (e.g., ViT, DETR, SAM);
- Expertise in image and video processing using OpenCV;
- Experience in model training, evaluation, and optimization;
- Fluent written and verbal communication skills in English.

Would be a plus:
- Experience applying ML techniques to embedded or resource-constrained environments (e.g. edge devices, mobile platforms, microcontrollers);
- Ideally, you have led projects where ML models were optimized, deployed, or fine-tuned for embedded systems, ensuring high performance and low latency under hardware limitations.

We offer:
- Free English classes with a native speaker and external courses compensation;
- PE support by professional accountants;
- 40 days of PTO;
- Medical insurance;
- Team-building events, conferences, meetups, and other activities;
- There are many other benefits you’ll find out at the interview.

We’re looking for a Senior Data Scientist to help shape how our clients build and scale AI solutions on AWS. In this role, you’ll develop and deploy cutting-edge generative AI models on SageMaker – from model training and fine-tuning to optimized deployment – guiding customers from ideation to production through proof of concept. You’ll work closely with startup founders, technical leaders, and account teams to create scalable, high-impact AI solutions that drive real business value.

Responsibilities:

• Model Development & Deployment: Deploy and train models on AWS SageMaker (using TensorFlow/PyTorch).
• Model Tuning & Optimization: Fine-tune and optimize models using techniques like quantization and distillation, and tools like Pruna.ai and Replicate.
• Generative AI Solutions: Design and implement advanced GenAI solutions, including prompt engineering and retrieval-augmented generation (RAG) strategies.
• LLM Workflows: Develop agentic LLM workflows that incorporate tool usage, memory, and reasoning for complex problem-solving.
• Scalability & Performance: Maximize model performance on AWS’s by leveraging techniques such as model compilation, distillation, and quantization and using AWS specific features.
• Collaboration: Work closely with Data Engineering, DevOps, and MLOps teams to integrate models into production pipelines and workflows.

Requirements:

• 4+ years of experience in machine learning or data science roles, with deep learning (NLP, LLMs) expertise.
• Expert in Python and deep learning frameworks (PyTorch/TensorFlow), and hands-on with AWS ML services (especially SageMaker and Bedrock).
• Proven experience with generative AI and fine-tuning large language models.
• Strong experience deploying ML solutions on AWS cloud infrastructure and familiarity with MLOps best practices.
• Excellent communication skills and ability to work directly with customers in a consulting capacity.
• A master’s degree in a relevant field and AWS ML certifications are a plus.

Benefits:

• Professional training and certifications covered by the company (AWS, FinOps, Kubernetes, etc.)
• International work environment
• Referral program – enjoy cooperation with your colleagues and get a bonus 
• Company events and social gatherings (happy hours, team events, knowledge sharing, etc.)
• English classes

• Soft skills training

   

Country-specific benefits will be discussed during the hiring process.

Automat-it is committed to fostering a workplace that promotes equal opportunities for all and believes that a diverse workforce is crucial to our success. Our recruitment decisions are based on your experience and skills, recognizing the value you bring to our team.

Quantum is a global technology partner delivering high-end software products that address real-world problems.

We advance emerging technologies for outside-the-box solutions. We focus on Machine Learning, Computer Vision, Deep Learning, GIS, MLOps, Blockchain, and more.

Here at Quantum, we are dedicated to creating state-of-art solutions that effectively address the pressing issues faced by businesses and the world. To date, our team of exceptional people has already helped many organizations globally attain technological leadership.

We constantly discover new ways to solve never-ending business challenges by adopting new technologies, even when there isn’t yet a best practice. If you share our passion for problem-solving and making an impact, join us and enjoy getting to know our wealth of experience!

About the position

Quantum is expanding the team and has brilliant opportunities for a Data Science Engineer. The client is a technological research company that utilizes proprietary AI-based analysis and language models to provide comprehensive insights into global stocks in all languages. Our mission is to bridge the knowledge gap in the investment world and empower investors of all types to become “super-investors.”

Through our generative AI technology implemented into brokerage platforms and other financial institutions’ infrastructures, we offer instant fundamental analyses of global stocks alongside bespoke investment strategies, enabling informed investment decisions for millions of investors worldwide.

Must have skills:

• At least 5 years of commercial experience in Data Science
• Strong knowledge of linear algebra, calculus, statistics, and probability theory
• Proficiency in algorithms and data structures
• Experience with Machine Learning libraries (NumPy, SciPy, Pandas, Scikit-learn)
• Experience with at least one Deep Learning framework (TensorFlow, Keras, or PyTorch)
• Knowledge of modern Neural Network architectures
• Experience in developing solutions with LLMs
• Experience with Cloud Computing Platforms (AWS, Google Cloud, or Azure)
• Practical experience with Docker
• Experience with SQL
• Strong understanding of Object-Oriented Programming (OOP) principles
• Hands-on experience in building solutions for financial domain
• At least an Upper-Intermediate level of English (spoken and written)

Would be a plus:

• Experience with MLOps solutions
• Basic understanding of Big Data concepts
• Experience in classical Computer Vision algorithms
• Participation in Kaggle competitions

Your tasks will include:

• Full-cycle data science projects
• Data analysis and data preparation
• Development of NLP/Deep Learning / Machine Learning; Developing models and deploying them to production
• Sometimes, this will require the ability to implement methods from scientific papers and apply them to new domains

We offer:

• Delivering high-end software projects that address real-world problems
• Surrounding experts who are ready to move forward professionally
• Professional growth plan and team leader support
• Taking ownership of R&D and socially significant projects
• Participation in worldwide tech conferences and competitions
• Taking part in regular educational activities
• Being a part of a multicultural company with a fun and lighthearted atmosphere
• Working from anywhere with flexible working hours
• Paid vacation and sick leave days

Join Quantum and take a step toward your data-driven future.

Kyivstar.Tech is seeking an experienced Senior Data Scientist / NLP Lead to spearhead the development of cutting-edge natural language processing solutions for our Ukrainian LLM project. You will lead our NLP team in designing, implementing, and deploying large-scale language models and NLP algorithms that power our products. This role is critical to our mission of advancing AI in the Ukrainian language context, and offers the opportunity to drive technical decisions, mentor a team of data scientists, and shape the future of AI capabilities in Ukraine.

About us

Kyivstar.Tech is a Ukrainian hybrid IT company and a resident of Diia.City.

We are a subsidiary of Kyivstar, one of Ukraine's largest telecom operators.

Our mission is to change lives in Ukraine and around the world by creating technological solutions and products that unleash the potential of businesses and meet users' needs.

Over 500+ KS.Tech specialists work daily in various areas: mobile and web solutions, as well as design, development, support, and technical maintenance of high-performance systems and services.

We believe in innovations that truly bring quality changes and constantly challenge conventional approaches and solutions. Each of us is an adherent of entrepreneurial culture, which allows us never to stop, to evolve, and to create something new.

What you will do 

• Lead end-to-end development of NLP and LLM models - from data exploration and model prototyping to validation and production deployment. This includes designing novel model architectures or fine-tuning state-of-the-art transformer models (e.g. BERT, GPT) to solve project-specific language tasks.

• Analyze large text datasets (Ukrainian and multilingual corpora) to extract insights and build robust training datasets. Guide data collection and annotation efforts to ensure high-quality data for model training.

• Develop and implement NLP algorithms for a range of tasks such as text classification, named entity recognition, semantic search, and conversational AI. Stay up-to-date with the latest research to apply transformer-based models, embeddings, and other modern NLP techniques in our solutions.

• Establish evaluation metrics and validation frameworks for model performance, including accuracy, factuality, and bias. Design A/B tests and statistical experiments to compare model variants and validate improvements.

• Deploy and integrate NLP models into production systems in collaboration with engineers - ensuring models are scalable, efficient, and well-monitored in a real-world setting. Optimize model inference and troubleshoot issues such as model drift or data pipeline bottlenecks.

• Provide technical leadership and mentorship to the NLP/ML team. Review code and research, uphold best practices in ML (version control, reproducibility, documentation), and foster a culture of continuous learning and innovation.

• Collaborate cross-functionally with product managers, software engineers, and MLOps engineers to align NLP solutions with product goals and infrastructure capabilities. Communicate complex data science concepts to stakeholders and incorporate their feedback into the model development process.

Qualifications and experience needed 

Education & Experience:

• 5+ years of experience in data science or machine learning, with a strong focus on NLP.

• Proven track record of developing and deploying NLP or ML models at scale in production environments.

• Advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning, or a related field is highly preferred.

NLP Expertise:

• Deep understanding of natural language processing techniques and algorithms.

• Hands-on experience with modern NLP approaches, including embedding models, text classification, sequence tagging (NER), and transformers/LLMs.

• Deep understanding of transformer architectures and knowledge of LLM training and fine-tuning techniques, hands-on experience developing solutions on LLM, and knowledge of linguistic nuances in Ukrainian or other languages.

Advanced NLP/ML Techniques:

•Experience with evaluation metrics for language models (perplexity, BLEU, ROUGE, etc.) and with techniques for model optimization (quantization, knowledge distillation) to improve efficiency.

•Background in information retrieval or RAG (Retrieval-Augmented Generation) is a plus for building systems that augment LLMs with external knowledge.

ML & Programming Skills:

•Proficiency in Python and common data science libraries (pandas, NumPy, scikit-learn).

•Strong experience with deep learning frameworks such as PyTorch or TensorFlow for building NLP models.

•Ability to write efficient, clean code and debug complex model issues.

Data & Analytics:

• Solid understanding of data analytics and statistics.

• Experience in experimental design, A/B testing, and statistical hypothesis testing to evaluate model performance.

• Experience in building a representative benchmarking framework given business requirements for LLM.

• Comfortable working with large datasets, writing complex SQL queries, and using data visualization to inform decisions.

Deployment & Tools:

• Experience deploying machine learning models in production (e.g., using REST APIs or batch pipelines) and integrating with real-world applications.

• Familiarity with MLOps concepts and tools (version control for models/data, CI/CD for ML).

• Experience with cloud platforms (AWS, GCP, or Azure) and big data technologies (Spark, Hadoop) for scaling data processing or model training is a plus.

• Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).

Leadership & Communication:

• Demonstrated ability to lead technical projects and mentor junior team members.

• Strong communication skills to convey complex ML results to non-technical stakeholders and to document methodologies.

A plus would be 

LLM training & evaluation experience:

• Experience with tokenizer development, SFT, and RLHF techniques.

• Knowledge of model safety: toxicity, hallucinations, ethical considerations, and LLM guardrails.

Research & Community:

• Publications in NLP/ML conferences or contributions to open-source NLP projects.

• Active participation in the AI community or demonstrated continuous learning (e.g., Kaggle competitions, research collaborations) indicating a passion for staying at the forefront of the field.

Domain & Language Knowledge:

• Familiarity with the Ukrainian language and cultural context for model training and evaluation.

MLOps & Infrastructure:

• Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).

• Experience in working alongside MLOps engineers to streamline the deployment and monitoring of NLP models.

Problem-Solving:

• Creative mindset for tackling open-ended AI challenges.

• Comfort in fast-paced R&D environments with evolving priorities.

What we offer

• Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace.

• Remote onboarding.

• Performance bonuses.

• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners.

• Health and life insurance.

• Wellbeing program and corporate psychologist.

• Reimbursement of expenses for Kyivstar mobile communication.

We are looking for a Computer Vision Engineer with an expertise in low-level CV algorithms.

Required Qualifications: 

• 5+ years of experience in computer vision
• Expert-level proficiency in Python
• Extensive experience in DL and PyTorch framework for CV stacks
• Understanding of geometrical computer vision principles
• Model optimization: quantization, pruning, neural network Compiler
• Hands-on experience in implementing low-level CV algorithms
• Knowledge of C++

Nice to Have:

• Experience with DL on edge devices
• Experience with SLAM and/or Visual-Inertial Odometry (VIO)
• Experience with sensor fusion (IMU, magnetometer, GNSS, camera)
• Familiarity with Kalman filters

About us:
Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with uniting top AI talents and organizing the first Data Science tech conference in Kyiv. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the client:
Our client is an IT company that develops technological solutions and products to help companies reach their full potential and meet the needs of their users. The team comprises over 600 specialists in IT and Digital, with solid expertise in various technology stacks necessary for creating complex solutions.

About the role:
We are looking for an experienced Senior/Middle Data Scientist with a passion for Large Language Models (LLMs) and cutting-edge AI research. In this role, you will focus on designing and prototyping data preparation pipelines, collaborating closely with data engineers to transform your prototypes into scalable production pipelines, and actively developing model training pipelines with other talented data scientists. Your work will directly shape the quality and capabilities of the models by ensuring we feed them the highest-quality, most relevant data possible.

Requirements:
Education & Experience:
- 3+ years of experience in Data Science or Machine Learning, preferably with a focus on NLP.
- Proven experience in data preprocessing, cleaning, and feature engineering for large-scale datasets of unstructured data (text, code, documents, etc.).
- Advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning, or a related field is highly preferred.
NLP Expertise:
- Good knowledge of natural language processing techniques and algorithms.
- Hands-on experience with modern NLP approaches, including embedding models, semantic search, text classification, sequence tagging (NER), transformers/LLMs, RAGs.
- Familiarity with LLM training and fine-tuning techniques.
ML & Programming Skills:
- Proficiency in Python and common data science and NLP libraries (pandas, NumPy, scikit-learn, spaCy, NLTK, langdetect, fasttext).
- Strong experience with deep learning frameworks such as PyTorch or TensorFlow for building NLP models.
- Ability to write efficient, clean code and debug complex model issues.
Data & Analytics:
- Solid understanding of data analytics and statistics.
- Experience in experimental design, A/B testing, and statistical hypothesis testing to evaluate model performance.
- Comfortable working with large datasets, writing complex SQL queries, and using data visualization to inform decisions.
Deployment & Tools:
- Experience deploying machine learning models in production (e.g., using REST APIs or batch pipelines) and integrating with real-world applications.
- Familiarity with MLOps concepts and tools (version control for models/data, CI/CD for ML).
- Experience with cloud platforms (AWS, GCP, or Azure) and big data technologies (Spark, Hadoop, Ray, Dask) for scaling data processing or model training.
Communication & Personality:
- Experience working in a collaborative, cross-functional environment.
- Strong communication skills to convey complex ML results to non-technical stakeholders and to document methodologies clearly.
- Ability to rapidly prototype and iterate on ideas

Nice to have:
Advanced NLP/ML Techniques:
- Familiarity with evaluation metrics for language models (perplexity, BLEU, ROUGE, etc.) and with techniques for model optimization (quantization, knowledge distillation) to improve efficiency.
- Understanding of FineWeb2 or similar processing pipelines approach.
Research & Community:
- Publications in NLP/ML conferences or contributions to open-source NLP projects.
- Active participation in the AI community or demonstrated continuous learning (e.g., Kaggle competitions, research collaborations) indicating a passion for staying at the forefront of the field.
Domain & Language Knowledge:
- Familiarity with the Ukrainian language and context.
- Understanding of cultural and linguistic nuances that could inform model training and evaluation in a Ukrainian context.
- Knowledge of Ukrainian text sources and data sets, or experience with multilingual data processing, can be an advantage given the project’s focus.
MLOps & Infrastructure:
- Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).
- Experience in working alongside MLOps engineers to streamline the deployment and monitoring of NLP models.
Problem-Solving:
- Innovative mindset with the ability to approach open-ended AI problems creatively.
- Comfort in a fast-paced R&D environment where you can adapt to new challenges, propose solutions, and drive them to implementation.

Responsibilities:
- Design, prototype, and validate data preparation and transformation steps for LLM training datasets, including cleaning and normalization of text, filtering of toxic content, de-duplication, de-noising, detection and deletion of personal data, etc.
- Formation of specific SFT/RLHF datasets from existing data, including data augmentation/labeling with LLM as teacher.
- Analyze large-scale raw text, code, and multimodal data sources for quality, coverage, and relevance.
- Develop heuristics, filtering rules, and cleaning techniques to maximize training data effectiveness.
- Collaborate with data engineers to hand over prototypes for automation and scaling.
- Research and develop best practices and novel techniques in LLM training pipelines.
- Monitor and evaluate data quality impact on model performance through experiments and benchmarks.
- Research and implement best practices in large-scale dataset creation for AI/ML models.
- Document methodologies and share insights with internal teams.

The company offers:
- Competitive salary.
- Equity options in a fast-growing AI company.
- Remote-friendly work culture.
- Opportunity to shape a product at the intersection of AI and human productivity.
- Work with a passionate, senior team building cutting-edge tech for real-world business use.

WE ARE

SoftServe is a global digital solutions company, headquartered in Austin, Texas, and founded in 1993.

With 2,000+ active projects across the USA, Europe, APAC, and LATAM, we deliver meaningful outcomes through bold thinking and deep expertise. Our people create impactful solutions, drive innovation, and genuinely enjoy what they do.

The AI and Data Science Center of Excellence (CoE) is SoftServe’s premier AI/ML hub, primarily based in Europe. With 130+ experts—including data scientists, research analysts, MLOps engineers, ML and LLM architects — we cover the full AI lifecycle, from problem framing to deployment.

In 2024, we delivered 150+ AI projects, including over 100 focused on Generative AI, combining scale with measurable impact.

We are a 2024 NVIDIA Service Delivery Partner and maintain strong collaborations with Google Cloud, Amazon, and Microsoft, ensuring our teams always work with cutting-edge tools and technologies.

We also lead Gen AI Lab — our internal innovation engine focused on applied research and cross-functional collaboration in Generative AI.

In 2025, a key area of innovation is Agentic AI — where we design and deploy autonomous, collaborative agent systems capable of addressing complex, real-world challenges at scale for our clients and internally.

IF YOU ARE

• Experienced in Generative AI and natural language processing (NLP), working with large-scale transformer models and generative pre-trained LLMs like GPT-4, Claude, and Gemini
• Knowledgeable about the latest advancements in diffusion models and other generative frameworks for text and image generation
• Adept at applying advanced deep learning techniques to practical use cases
• Well-versed in emerging trends and breakthroughs in machine learning, deep learning, and NLP, with a strong focus on their real-world applications
• Proficient in working with state-of-the-art pre-trained language models like GPT-4 and BERT, including fine-tuning for specialized tasks
• Aware of the software development lifecycle for AI projects and the operationalization of machine learning models
• Experienced in deploying AI solutions on major cloud platforms
• Hands-on with Python and deep learning frameworks such as TensorFlow or PyTorch
• Skilled in interpersonal communication, analytical reasoning, and complex problem-solving
• Capable of translating technical concepts into clear, concise insights that non-technical audiences can easily grasp
• Proficient in business communication in English at an upper-intermediate level
   

AND YOU WANT TO

• Work with the full stack of data analysis, deep learning, and machine learning model pipeline that includes deep analysis of customer data, modeling, and deployment in production
• Choose relevant computational tools for study, experiment, or trial research objectives
• Drive the development of innovative solutions for language generation, text synthesis, and creative content generation using the latest state-of-the-art techniques
• Develop and implement advanced Generative AI solutions such as intelligent assistants, Retrieval-Augmented Generation (RAG) systems, and other innovative applications
• Produce clear, concise, well-organized, and error-free computer programs with the appropriate technological stack
• Present results directly to stakeholders and gather business requirements
• Develop expertise in state-of-the-art Generative AI techniques and methodologies
• Grow your skill set within a dynamic and supportive environment
• Work with Big Data solutions and advanced data tools in cloud platforms
• Build and operationalize ML models, including data manipulation, experiment design, developing analysis plans, and generating insights
• Lead teams of data scientists and software engineers to successful project execution

TOGETHER WE WILL

• Be part of a team that's shaping the future of AI and data science through innovation and shared growth.
• Advance the frontier of Agentic AI by shaping intelligent multi-agent ecosystems that drive autonomy, scalability, and measurable business value.
• Have access to world-class training, cutting-edge research, and collaborate with top industry partners.
• Maintain a synergy of Data Scientists, DevOps team, and ML Engineers to build infrastructure, set up processes, productize machine learning pipelines, and integrate them into existing business environments
• Communicate with the world-leading companies from our logos portfolio
• Enjoy the opportunity to work with the latest modern tools and technologies on various projects
• Participate in international events and get certifications in cutting-edge technologies
• Have access to powerful educational and mentorship programs
• Revolutionize the software industry and drive innovation in adaptive self-learning technologies by leveraging multidisciplinary expertise

United Tech is a global IT product company shaping the future of real-time social connection.

With millions of users across North America, Europe, LATAM, and MENA, we build next-gen mobile and web apps for live-streaming and social networking.

Our platforms enable connection at scale fast, interactive, and deeply engaging.

The market is projected to exceed $206B by 2030, and we are already leading the evolution.

Founded in Ukraine, scaling worldwide. Are you in?

About the role: This is a role for a leader who thrives in a fast-moving product environment, where challenges fuel growth and every decision shapes the future. With United Tech you will have the freedom to design, build, and re-engineer processes from the ground up, working side by side with a team that values initiative, knowledge sharing, and bold goals. Your ideas will directly influence revenue, and you will see the tangible results of your work reflected in key financial metrics. We move fast, we cut through bureaucracy, and we take on complex challenges that push both personal and professional boundaries, limited only by the scale of your ambitions

In this role, you will

• Build, scale, and develop the Data Science team, including hiring, mentoring, and performance evaluation
• Define and execute a Data Science strategy aligned with business priorities
• Oversee the full lifecycle of DS projects from problem formulation to deploying models into production
• Prioritize initiatives based on business impact (ROI, time-to-market)
• Collaborate closely with product managers, analysts, engineers, and C-level executives

It’s all about you

• Proven ability to implement best practices in Data Science: reproducibility, A/B testing, ML monitoring
• Strong track record in maintaining model quality (performance, drift, latency)
• Advanced Python skills (pandas, sklearn, numpy, xgboost; pytorch/tf is a plus)
• High-level SQL expertise (large datasets, query optimization)
  Hands-on experience with ML pipelines, orchestration (Airflow, Prefect), and monitoring (Evidently, MLflow, Prometheus)
• Experience with GCP
• Solid understanding of A/B testing, causal inference, and statistics
• Familiarity with architecture fundamentals (API, data pipelines, microservices — integration level)
• Cloud experience with AWS or Azure
• Knowledge of distributed computation tools (e.g., Spark, CloudRun)
• Proven track record with generative AI/NLP model deployment
• Experience in startups or high-growth companies
• Publications, conference speaking, achievements on Kaggle, or open-source contributions

Would be a plus

• Experience optimizing company processes through AI solutions
• Implementation of AI tools across departments (development, support, marketing, etc.)

What we offer

Care and support: 

• 20 paid vacation days, 15 sick days, and 6 additional days off for family events
• Up to 10 additional days off for public holidays
• 100% medical insurance coverage
• Sports and equipment reimbursement
• Team building events, corporate gifts, and stylish merch
• Financial and legal support
• Position retention and support for those who join the Armed Forces of Ukraine
• Participation in social initiatives supporting Ukraine
   

Comfortable working environment:

• Work from our Kyiv hub or remotely with a flexible schedule 
• Workspace rental reimbursement in other cities and abroad
• Modern equipment or depreciation of your own tools
   

Investment in your future:

• Collaborate with a highly-skilled team of Middle & Senior professionals, sharing practical cases and expertise in the social networking niche
• 70% of our heads and leads have grown into their roles here – so can you!
• Performance-oriented reviews and Individual Development Plans (IDPs)
• Reimbursement for professional courses and English classes
• Corporate library, book club, and knowledge-sharing events
   

Hiring process

• Intro call
• Technical Interview
• Interview with Hiring Manager
• Final Interview
• Reference check
• Offer

Join us at Provectus to be a part of a team that is dedicated to building cutting-edge technology solutions that have a positive impact on society. Our company specializes in AI and ML technologies, cloud services, and data engineering, and we take pride in our ability to innovate and push the boundaries of what's possible.

As an ML Engineer, you’ll be provided with all opportunities for development and growth.

Let's work together to build a better future for everyone!
 

Requirements:

• Comfortable with standard ML algorithms and underlying math.
• Strong hands-on experience with LLMs in production, RAG architecture, and agentic systems
• AWS Bedrock experience strongly preferred
• Practical experience with solving classification and regression tasks in general, feature engineering.
• Practical experience with ML models in production.
• Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.
• Solid software engineering skills (i.e., ability to produce well-structured modules, not only notebook scripts).
• Python expertise, Docker.
• English level - strong Intermediate.
• Excellent communication and problem-solving skills.
   

Will be a plus:

• Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda).
• Practical experience with deep learning models.
• Experience with taxonomies or ontologies.
• Practical experience with machine learning pipelines to orchestrate complicated workflows.
• Practical experience with Spark/Dask, Great Expectations.
   

Responsibilities:

• Create ML models from scratch or improve existing models. 
• Collaborate with the engineering team, data scientists, and product managers on production models.
• Develop experimentation roadmap. 
• Set up a reproducible experimentation environment and maintain experimentation pipelines.
• Monitor and maintain ML models in production to ensure optimal performance.
• Write clear and comprehensive documentation for ML models, processes, and pipelines.
• Stay updated with the latest developments in ML and AI and propose innovative solutions.

We are seeking an experienced Senior/Middle Data Scientist with a passion for large language models (LLMs) and cutting-edge AI research. In this role, you will design and implement a state-of-the-art evaluation and benchmarking framework to measure and guide model quality, and personally train LLMs with a strong focus on Reinforcement Learning from Human Feedback (RLHF). You will work alongside top AI researchers and engineers, ensuring our models are not only powerful but also aligned with user needs, cultural context, and ethical standards. The benchmarks and feedback loops you own serve as the contract for quality—gating releases, catching regressions before users do, and enabling compliant, trustworthy features to ship with confidence.

What you will do

• Analyze benchmarking datasets, define gaps, and design, implement, and maintain a comprehensive benchmarking framework for the Ukrainian language.
• Research and integrate state-of-the-art evaluation metrics for factual accuracy, reasoning, language fluency, safety, and alignment.
• Design and maintain testing frameworks to detect hallucinations, biases, and other failure modes in LLM outputs.
• Develop pipelines for synthetic data generation and adversarial example creation to challenge the model’s robustness.
• Collaborate with human annotators, linguists, and domain experts to define evaluation tasks and collect high-quality feedback.
• Develop tools and processes for continuous evaluation during model pre-training, fine-tuning, and deployment.
• Research and develop best practices and novel techniques in LLM training pipelines.
• Analyze benchmarking results to identify model strengths, weaknesses, and improvement opportunities.
• Work closely with other data scientists to align training and evaluation pipelines.
• Document methodologies and share insights with internal teams.

Qualifications and experience needed

Education & Experience:

• 3+ years of experience in Data Science or Machine Learning, preferably with a focus on NLP.
• Proven experience in machine learning model evaluation and/or NLP benchmarking.
• An advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning, or a related field is highly preferred.

NLP Expertise:

• Good knowledge of natural language processing techniques and algorithms.
• Hands-on experience with modern NLP approaches, including embedding models, semantic search, text classification, sequence tagging (NER), transformers/LLMs, RAGs.
• Familiarity with LLM training and fine-tuning techniques.

ML & Programming Skills:

• Proficiency in Python and common data science and NLP libraries (pandas, NumPy, scikit-learn, spaCy, NLTK, langdetect, fasttext).
• Strong experience with deep learning frameworks such as PyTorch or TensorFlow for building NLP models.
• Solid understanding of RLHF concepts and related techniques (preference modeling, reward modeling, reinforcement learning).
• Ability to write efficient, clean code and debug complex model issues.

Data & Analytics:

• Solid understanding of data analytics and statistics.
• Experience creating and managing test datasets, including annotation and labeling processes.
• Experience in experimental design, A/B testing, and statistical hypothesis testing to evaluate model performance.
• Comfortable working with large datasets, writing complex SQL queries, and using data visualization to inform decisions.

Deployment & Tools:

• Experience deploying machine learning models in production (e.g., using REST APIs or batch pipelines) and integrating with real-world applications.
• Familiarity with MLOps concepts and tools (version control for models/data, CI/CD for ML).
• Experience with cloud platforms (AWS, GCP, or Azure) and big data technologies (Spark, Hadoop, Ray, Dask) for scaling data processing or model training is a plus.

Communication:

• Experience working in a collaborative, cross-functional environment.
• Strong communication skills to convey complex ML results to non-technical stakeholders and to document methodologies.

A plus would be

Advanced NLP/ML Techniques:

• Prior work on LLM safety, fairness, and bias mitigation.
• Familiarity with evaluation metrics for language models (perplexity, BLEU, ROUGE, etc.) and with techniques for model optimization (quantization, knowledge distillation) to improve efficiency.
• Knowledge of data annotation workflows and human feedback collection methods.

Research & Community:

• Publications in NLP/ML conferences or contributions to open-source NLP projects.
• Active participation in the AI community or demonstrated continuous learning (e.g., Kaggle competitions, research collaborations) indicates a passion for staying at the forefront of the field.

Domain & Language Knowledge:

• Familiarity with the Ukrainian language and context.
• Understanding of cultural and linguistic nuances that could inform model training and evaluation in a Ukrainian context.
• Knowledge of Ukrainian benchmarks, or familiarity with other evaluation datasets and leaderboards for large models, can be an advantage given our project’s focus.

MLOps & Infrastructure:

• Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).
• Experience in working alongside MLOps engineers to streamline the deployment and monitoring of NLP models.

Problem-Solving:

• Innovative mindset with the ability to approach open-ended AI problems creatively.
• Comfort in a fast-paced R&D environment where you can adapt to new challenges, propose solutions, and drive them to implementation.

What we offer:

• Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace.
• Remote onboarding.
• Performance bonuses for everyone (annual or quarterly — depends on the role).
• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners. 
• Health and life insurance.
• Wellbeing program and corporate psychologist.
• Reimbursement of expenses for Kyivstar mobile communication.

We are seeking an experienced Senior/Middle Data Scientist with a passion for large language models (LLMs) and cutting-edge AI research. In this role, you will focus on designing and prototyping data preparation pipelines, collaborating closely with data engineers to transform your prototypes into scalable production pipelines and actively develop model training pipelines with other talented data scientists. Your work will directly shape the quality and capabilities of our models by ensuring we feed them the highest-quality, most relevant data possible. The datasets you build directly determine model capability, safety, and cost, raising downstream task accuracy, reducing training waste, and accelerating time-to-market for product teams.

What you will do

• Design, prototype, and validate data preparation and transformation steps for LLM training datasets, including cleaning and normalization of text, filtering of toxic content, de-duplication, de-noising, detection and deletion of personal data, etc.
• Formation of specific SFT/RLHF datasets from existing data, including data augmentation/labeling with LLM as teacher.
• Analyze large-scale raw text, code, and multimodal data sources for quality, coverage, and relevance.
• Develop heuristics, filtering rules, and cleaning techniques to maximize training data effectiveness.
• Collaborate with data engineers to hand over prototypes for automation and scaling.
• Research and develop best practices and novel techniques in LLM training pipelines.
• Monitor and evaluate data quality impact on model performance through experiments and benchmarks.
• Research and implement best practices in large-scale dataset creation for AI/ML models.
• Document methodologies and share insights with internal teams.

Qualifications and experience needed

Education & Experience:

• 3+ years of experience in Data Science or Machine Learning, preferably with a focus on NLP.
• Proven experience in data preprocessing, cleaning, and feature engineering for large-scale datasets of unstructured data (text, code, documents, etc.).
• An advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning, or a related field is highly preferred.

NLP Expertise:

• Good knowledge of natural language processing techniques and algorithms.
• Hands-on experience with modern NLP approaches, including embedding models, semantic search, text classification, sequence tagging (NER), transformers/LLMs, RAGs.
• Familiarity with LLM training and fine-tuning techniques, and data requirements.

ML & Programming Skills:

• Proficiency in Python and common data science and NLP libraries (pandas, NumPy, scikit-learn, spaCy, NLTK, langdetect, fasttext).
• Strong experience with deep learning frameworks such as PyTorch or TensorFlow for building NLP models.
• Ability to write efficient, clean code and debug complex model issues.

Data & Analytics:

• Solid understanding of data analytics and statistics.
• Experience in experimental design, A/B testing, and statistical hypothesis testing to evaluate model performance.
• Comfortable working with large datasets, writing complex SQL queries, and using data visualization to inform decisions.

Deployment & Tools:

• Experience deploying machine learning models in production (e.g., using REST APIs or batch pipelines) and integrating with real-world applications.
• Familiarity with MLOps concepts and tools (version control for models/data, CI/CD for ML).
• Experience with cloud platforms (AWS, GCP, or Azure) and big data technologies (Spark, Hadoop, Ray, Dask) for scaling data processing or model training is a plus.

Communication & Personality:

• Experience working in a collaborative, cross-functional environment.
• Strong communication skills to convey complex ML results to non-technical stakeholders and to document methodologies.
• Ability to rapidly prototype and iterate on ideas

A plus would be

Advanced NLP/ML Techniques:

• Familiarity with evaluation metrics for language models (perplexity, BLEU, ROUGE, etc.) and with techniques for model optimization (quantization, knowledge distillation) to improve efficiency.
• Understanding of FineWeb2 or a similar processing pipeline approach

Research & Community:

• Publications in NLP/ML conferences or contributions to open-source NLP projects.
• Active participation in the AI community or demonstrated continuous learning (e.g., Kaggle competitions, research collaborations)

Domain & Language Knowledge:

• Familiarity with the Ukrainian language and context.
• Understanding of cultural and linguistic nuances that could inform model training and evaluation in a Ukrainian context.
• Knowledge of Ukrainian text sources and data sets, or experience with multilingual data processing, can be an advantage given our project’s focus.

MLOps & Infrastructure:

• Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).
• Experience in working alongside MLOps engineers to streamline the deployment and monitoring of NLP models.

Problem-Solving:

• Innovative mindset with the ability to approach open-ended AI problems creatively.
• Comfort in a fast-paced R&D environment where you can adapt to new challenges, propose solutions, and drive them to implementation.

What we offer

• Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace.
• Remote onboarding.
• Performance bonuses.
• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners.
• Health and life insurance.
• Wellbeing program and corporate psychologist.
• Reimbursement of expenses for Kyivstar mobile communication.