Jobs Data Science

Azzurro.io is looking for ML Engineer.

Location: Remote (Company based in Seattle)

About the Client: Our client partners with brands to improve their sales and visibility on Amazon through optimized advertising campaigns and keyword strategies. Using data-driven insights, they help clients increase their impact in the marketplace.

Role Overview: As a Data Scientist, you'll build predictive models using time series data (e.g., product ranks, keyword performance, ad campaigns) to help optimize our client’s Amazon strategies. You’ll analyze, clean, and transform data to train ML models that improve ad performance and drive sales.

Responsibilities:

• Predictive Modeling: Develop and refine models to analyze product rankings and campaign performance.
• Data Preparation: Extract, clean, and transform large datasets for analysis and modeling.
• Regression Analysis: Build regression models to forecast trends and improve keyword strategies.
• Model Optimization: Use techniques like feature engineering and hyperparameter tuning to improve model performance.

Tech Stack:

• Core Technologies: AWS, MySQL, Python.
• Data & ML Tools: Python libraries (NumPy, pandas), frameworks (e.g., TensorFlow or similar).

Qualifications:

• Strong background in analytics, mathematics, and experience with time series data.
• Proficiency in Python, including data libraries (NumPy, pandas) and ML frameworks (e.g., TensorFlow, PyTorch).
• Experience building regression models and optimizing predictive algorithms.
• Working knowledge of SQL for querying large datasets.
  
  P.S. please pay your attention that this position is open in Azzurro.io company, not Pics.io.

We are seeking a highly skilled Machine Learning (ML) Tech Lead with a strong background in Large Language Models (LLMs) and AWS Cloud services. The ideal candidate will oversee the development and deployment of cutting-edge AI solutions while managing a team of 5-10 engineers. This leadership role demands hands-on technical expertise, strategic planning, and team management capabilities to deliver innovative products at scale.
 

Responsibilities:

• Leadership & Management
  -Lead and manage a team of 5-10 engineers, providing mentorship and fostering a collaborative team environment;
  -Drive the roadmap for machine learning projects aligned with business goals;
  -Coordinate cross-functional efforts with product, data, and engineering teams to ensure seamless delivery.
• Machine Learning & LLM Expertise
  -Design, develop, and fine-tune LLMs and other machine learning models to solve business problems;
  -Evaluate and implement state-of-the-art LLM techniques for NLP tasks such as text generation, summarization, and entity extraction;
  -Stay ahead of advancements in LLMs and apply emerging technologies;
  -Expertise in multiple main fields of ML: NLP, Computer Vision, RL, deep learning and classical ML.
• AWS Cloud Expertise
  -Architect and manage scalable ML solutions using AWS services (e.g., SageMaker, Lambda, Bedrock, S3, ECS, ECR, etc.);
  -Optimize models and data pipelines for performance, scalability, and cost-efficiency in AWS;
  -Ensure best practices in security, monitoring, and compliance within the cloud infrastructure.
• Technical Execution
  -Oversee the entire ML lifecycle, from research and experimentation to production and maintenance;
  -Implement MLOps and LLMOps practices to streamline model deployment and CI/CD workflows;
  -Debug, troubleshoot, and optimize production ML models for performance.
• Team Development & Communication
  -Conduct regular code reviews and ensure engineering standards are upheld;
  -Facilitate professional growth and learning for the team through continuous feedback and guidance;
  -Communicate progress, challenges, and solutions to stakeholders and senior leadership.
  
  Qualifications:
• Proven experience with LLMs and NLP frameworks (e.g., Hugging Face, OpenAI, or Anthropic models);
• Strong expertise in AWS Cloud Services;
• Strong experience in ML/AI, including at least 2 years in a leadership role;
• Hands-on experience with Python, TensorFlow/PyTorch, and model optimization;
• Familiarity with MLOps tools and best practices;
• Excellent problem-solving and decision-making abilities;
• Strong communication skills and the ability to lead cross-functional teams;
• Passion for mentoring and developing engineers.

Responsibilities

Model Fine-Tuning and Deployment:

Fine-tune pre-trained models (e.g., BERT, GPT) for specific tasks and deploy them using Amazon SageMaker and Bedrock.

RAG Workflows:

Establish Retrieval-Augmented Generation (RAG) workflows that leverage knowledge bases built on Kendra or OpenSearch. This includes integrating various data sources, such as corporate documents, inspection checklists, and real-time external data feeds.

MLOps Integration:

The project includes a comprehensive MLOps framework to manage the end-to-end lifecycle of machine learning models. This includes continuous integration and delivery (CI/CD) pipelines for model training, versioning, deployment, and monitoring. Automated workflows ensure that models are kept up-to-date with the latest data and are optimized for performance in production environments.

Scalable and Customizable Solutions:

Ensure that both the template and ingestion pipelines are scalable, allowing for adjustments to meet specific customer needs and environments. This involves setting up RAG workflows, knowledge bases using Kendra/OpenSearch, and seamless integration with customer data sources.

End-to-End Workflow Automation:

Automate the end-to-end process from user input to response generation, ensuring that the solution leverages AWS services like Bedrock Agents, CloudWatch, and QuickSight for real-time monitoring and analytics.

Advanced Monitoring and Analytics:

Integrated with AWS CloudWatch, QuickSight, and other monitoring tools, the accelerator provides real-time insights into performance metrics, user interactions, and system health. This allows for continuous optimization of service delivery and rapid identification of any issues.

Model Monitoring and Maintenance:

Implement model monitoring to track performance metrics and trigger retraining as necessary.

Collaboration:

Work closely with data engineers and DevOps engineers to ensure seamless integration of models into the production pipeline.

Documentation:

Document model development processes, deployment procedures, and monitoring setups for knowledge sharing and future reference.

Must-Have Skills

Machine Learning: Strong experience with machine learning frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.

MLOps Tools: Proficiency with Amazon SageMaker for model training, deployment, and monitoring.

Document processing: Experience with document processing for Word, PDF, images.

OCR: Experience with OCR tools like Tesseract / AWS Textract (preferred)

Programming: Proficiency in Python, including libraries such as Pandas, NumPy, and Scikit-Learn.

Model Deployment: Experience with deploying and managing machine learning models in production environments.

Version Control: Familiarity with version control systems like Git.

Automation: Experience with automating ML workflows using tools like AWS Step Functions or Apache Airflow.

Agile Methodologies: Experience working in Agile environments using tools like Jira and Confluence.

Nice-to-Have Skills

LLM: Experience with LLM / GenAI models, LLM Services (Bedrock or OpenAI), LLM abstraction like (Dify, Langchain, FlowiseAI), agent frameworks, rag.

Deep Learning: Experience with deep learning models and techniques.

Data Engineering: Basic understanding of data pipelines and ETL processes.

Containerization: Experience with Docker and Kubernetes (EKS).

Serverless Architectures: Experience with AWS Lambda and Step Functions.

Rule engine frameworks: Like Drools or similar

If you are a motivated individual with a passion for ML and a desire to contribute to a dynamic team environment, we encourage you to apply for this exciting opportunity. Join us in shaping the future of infrastructure and driving innovation in software delivery processes.

We are seeking a highly skilled Machine Learning (ML) Tech Lead with a strong background in Large Language Models (LLMs) and AWS Cloud services. The ideal candidate will oversee the development and deployment of cutting-edge AI solutions while managing a team of 5-10 engineers. This leadership role demands hands-on technical expertise, strategic planning, and team management capabilities to deliver innovative products at scale.
 

Responsibilities:

• Leadership & Management
  -Lead and manage a team of 5-10 engineers, providing mentorship and fostering a collaborative team environment;
  -Drive the roadmap for machine learning projects aligned with business goals;
  -Coordinate cross-functional efforts with product, data, and engineering teams to ensure seamless delivery.
• Machine Learning & LLM Expertise
  -Design, develop, and fine-tune LLMs and other machine learning models to solve business problems;
  -Evaluate and implement state-of-the-art LLM techniques for NLP tasks such as text generation, summarization, and entity extraction;
  -Stay ahead of advancements in LLMs and apply emerging technologies;
  -Expertise in multiple main fields of ML: NLP, Computer Vision, RL, deep learning and classical ML.
• AWS Cloud Expertise
  -Architect and manage scalable ML solutions using AWS services (e.g., SageMaker, Lambda, Bedrock, S3, ECS, ECR, etc.);
  -Optimize models and data pipelines for performance, scalability, and cost-efficiency in AWS;
  -Ensure best practices in security, monitoring, and compliance within the cloud infrastructure.
• Technical Execution
  -Oversee the entire ML lifecycle, from research and experimentation to production and maintenance;
  -Implement MLOps and LLMOps practices to streamline model deployment and CI/CD workflows;
  -Debug, troubleshoot, and optimize production ML models for performance.
• Team Development & Communication
  -Conduct regular code reviews and ensure engineering standards are upheld;
  -Facilitate professional growth and learning for the team through continuous feedback and guidance;
  -Communicate progress, challenges, and solutions to stakeholders and senior leadership.
  
  Qualifications:
• Proven experience with LLMs and NLP frameworks (e.g., Hugging Face, OpenAI, or Anthropic models);
• Strong expertise in AWS Cloud Services;
• Strong experience in ML/AI, including at least 2 years in a leadership role;
• Hands-on experience with Python, TensorFlow/PyTorch, and model optimization;
• Familiarity with MLOps tools and best practices;
• Excellent problem-solving and decision-making abilities;
• Strong communication skills and the ability to lead cross-functional teams;
• Passion for mentoring and developing engineers.

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.

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.

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 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 SLAM, Visual-Inertial Odometry (VIO), and sensor fusion.

We consider engineers at Middle/Senior levels — tasks and responsibilities will be adjusted accordingly.

Required Qualifications:

• 3+ years of hands-on experience with classical computer vision
• Knowledge of popular computer vision networks and components 
• Understanding of geometrical computer vision principles
• Hands-on experience in implementing low-level CV algorithms
• Practical experience with SLAM and/or Visual-Inertial Odometry (VIO)
• Proficiency in C++
• Experience with Linux
• Ability to quickly navigate through recent research and trends in computer vision.
• Relevant work experience or education in STEM field

Nice to Have:

• Experience with Python
• Familiarity with neural networks and common CV frameworks/libraries (OpenCV, NumPy, PyTorch, ONNX, Eigen, etc.)
• Experience with sensor fusion.

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 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

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

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.

Automat-it is where high-growth startups turn when they need to move faster, scale smarter, and make the most of the cloud. As an AWS Premier Partner and Strategic Partner, we deliver hands-on DevOps, FinOps, and GenAI solutions that drive real results. We work across EMEA and the US, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.

We’re looking for a hands-on Data Science Team Lead to build and scale production AI/ML solutions on AWS while leading a Data Scientist team. You’ll own the full lifecycle —from discovery and proof-of-concepts to training, optimization, deployment, and iteration in production — partnering closely with customers and cross-functional teams.

If you are interested in this opportunity, please submit your CV in English.

Responsibilities

• People leadership: Manage and coach a team of Data Scientists, set clear goals, run 1:1s, and support career growth and technical excellence.
• Delivery ownership: Drive project scoping, planning, and on-time, high-quality delivery from inception to production. Proactively remove blockers, manage risks, and communicate status to stakeholders.
• Customer engagement: Work directly with founders/technical leaders to understand goals, translate them into feasible AI roadmaps, and ensure measurable business outcomes.
• 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 other teams (Data Engineering, DevOps, MLOps, Solution Architects, Sales teams) to integrate models into production pipelines and workflows.

   

Requirements

• Team management experience: 2+ years leading engineers or scientists (people or tech lead).
• Technical experience: 5–6+ years in Data Science/ML (including deep learning/LLMs).
• Excellent customer-facing skills to understand and address client needs effectively.
• 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.
• Experience deploying ML solutions on AWS cloud infrastructure and familiarity with MLOps best practices.
• Fluent written and verbal communication skills in English.

• 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.

We’re looking for a proactive Data Scientist to join our growing team and help us redefine the future of eSports betting! You will develop and implement advanced models for esports betting, focusing on games such as Dota 2, League of Legends, etc. Oversee the entire model development lifecycle, including design, testing, and performance optimization.

What you’ll be doing:

• Develop and implement betting models using Python and Golang.
• Design and optimize mathematical models, including statistical models, classical machine learning techniques, and neural networks.
• Analyze the performance and impact of models, ensuring operational efficiency.
• Prototype and assess models to evaluate their effectiveness and user acceptance.
• Integrate models with existing systems and optimize performance.
• Collaborate with backend and frontend teams for seamless implementation and decision-making.
• Conduct in-depth statistical analysis and apply machine learning methods to enhance forecasting accuracy.

What we’re looking for:

• 3+ years of commercial experience with Python.
• Strong knowledge of statistics and practical experience with ML techniques.
• Proven expertise in mathematical modeling, including statistical methods, classical ML approaches, and neural networks.
• Strong data processing skills (validation, parsing, visualization).
• Understanding business logic of decisions and analytical thinking ability.
• Excellent communication skills and the ability to work in a team.
• Ability to assess the business value of tasks.
• English – Intermediate level.
• Nice to have: Higher education in computer science, mathematics, statistics, or a related discipline is a plus.

• Nice to have: Experience in the betting industry or related fields is an advantage.

   

What We Offer:

• Your wellbeing and a comfortable work environment are our top priorities:
• Flexible schedule & work format (office/hybrid): work where and when you feel most productive.
• 20 paid + 15 unpaid vacation days: take time off whenever you need to reset.
• An extra day off on your birthday — celebrate it your way!
• Medical insurance: take care of your health with extended coverage (available in Ukraine only).
• 22 sick days: 8 days without a doctor’s note (for sick leave or mental health), 10 with a note, plus 4 Personal Days per year — for personal matters, when it is necessary.
• Gifts and bonuses for life’s big moments: weddings, new babies, kindergarten support (available in Ukraine only).

Who We Are:

We’re DATA.BET — a product-driven IT company transforming the world of sports, esports, and virtual betting with our innovative sportsbook solution. 

Since 2017, we’ve been building tech that directly shapes the industry.
Our team of experts blends hands-on experience with AI technologies to deliver cutting-edge solutions that set new standards in betting.

Join Burny Games — a Ukrainian company that creates mobile puzzle games. Our mission is to create top-notch innovative games to challenge players’ minds daily.

What makes us proud?

• In just two years, we’ve launched two successful mobile games worldwide: Playdoku and Colorwood Sort. We have paused some projects to focus on making our games better and helping our team improve.
• Our games have been enjoyed by over 45 million players worldwide, and we keep attracting more players.
• We’ve created a culture where we make decisions based on data, which helps us grow every month.
• We believe in keeping things simple, focusing on creativity, and always searching for new and effective solutions.

What are you working on?

• Genres: Puzzle, Casual
• Platforms: Mobile, iOS, Android, Social

Team size and structure?

130+ employees

Key Responsibilities:

• Build and maintain ML for product and marketing teams
• Develop predictive systems for personalization, recommendations, and dynamic game content
• Automate data workflows and create reliable, scalable ML pipelines from feature engineering to deployment
• Monitor model performance, detect drift, and ensure ongoing accuracy and stability of ML systems
• Partner with Product, Marketing, and Engineering to integrate ML solutions into live games and operational workflows
• Own DS/ML projects end-to-end: from defining the problem to production deployment and iteration
• Share knowledge, conduct code reviews, and promote best practices across the data team

About You:

• 4+ years of experience in Data Science or ML, with a track record of delivering production models (2+ years in gamedev or consumer apps businesses)
• Strong background in statistical modeling, forecasting, and machine learning
• Advanced programming skills in Python or R (pandas, numpy, scikit-learn, PyTorch/TensorFlow or tidyverse, caret, mlr), writing clean and maintainable code
• Excellent SQL skills, confident with large-scale datasets and cloud data warehouses (BigQuery, Snowflake, Redshift)
• Experience deploying, monitoring, and maintaining ML models in production environments
• Strong problem-solving mindset, able to translate business and product goals into ML solutions
• Clear communicator who can explain complex models and systems to both technical and non-technical teams
• Passion for gaming and curiosity about player behavior

Will Be a Plus:

• Experience building user-level LTV forecasting models
• Background in recommender systems, personalization, or contextual bandits
• Familiarity with MLOps practices and tools
• Experience with ETL/orchestration frameworks (dbt, Dataform, Airflow)
• We run on GCP — experience with BigQuery, Vertex AI, Pub/Sub, and Cloud Run/Functions

What we offer:

• 100% payment of vacations and sick leave [20 days vacation, 22 days sick leave], medical insurance.
• A team of the best professionals in the games industry.
• Flexible schedule [start of work from 8 to 11, 8 hours/day].
• L&D center with courses.
• Self-learning library, access to paid courses.
• Stable payments.

The recruitment process:

CV review → Interview with TA manager → Interview with Head of Analytics → Final Enterview → Job offer

If you share our goals and values and are eager to join a team of dedicated professionals, we invite you to take the next step.