Jobs

Position Overview

DataObrii, a dynamic Data Science company based in the UK, is seeking an experienced Project Manager/Team Lead (Data Science) to join our team full-time remotely. We are looking for candidates with strong technical expertise in data science (!) who are adept at project-centric approaches and fostering growth opportunities for both projects and technical aspects. In this position you will be pivotal in overseeing and managing Data Science projects, ensuring their successful delivery within scope, timeline, and budget. 

Key Responsibilities:

• Prioritize and plan task execution, ensuring alignment with project objectives and timelines.
• Help to solve technical issues and unblock project members, helping to solve and guide the team through various complex day-to-day challenges in data science
• Coordinate project team members, distribute workload effectively, and assign tasks based on expertise and capacity.
• Verify completed tasks to ensure compliance with project requirements and quality standards.
• Utilize management tools to track project progress against established timelines, making adjustments as needed to maintain schedule adherence.
• Identify and address issues or obstacles during project execution.
• Monitor work performance, identify areas for improvement, and implement optimizations using Monday dashboards.
• Communicate project progress, updates, and risks to senior management through regular and concise reporting.
• Maintain accurate and up-to-date project documentation to facilitate transparency and knowledge sharing among team members.

• Foster a healthy work environment, promoting teamwork and collaboration among team members.

   

  Required Skills and Qualifications:

1. At least 2 years of proven full-time experience working as a Data Scientist/Team Lead in Data Science.
2. Proficiency in conducting and managing Data Science projects.
3. Strong technical expertise:

• Proficiency in building custom neural networks using PyTorch or TensorFlow.
• Experience with tree-based models.
• Strong expertise with various neural network architectures (recurrent, convolutional, feedforward, etc.).
• In-depth knowledge of Python programming and relevant libraries (e.g., Scikit-learn, Pandas, PyTorch, Shap).
• Solid understanding of statistics and data analysis.
• Experience with time series data, including loading, cleaning, and feature engineering using libraries like pandas, numpy, and Darts.
• Proficiency with neural network layers (e.g. LSTM, GRU, Conv1D, Dense, Dropout, BatchNormalization, residual layers) and activation functions (ReLU, Sigmoid, Tanh, Softmax, etc.).
• Skilled in using and tuning loss functions such as MSE, MAPE and custom loss functions relevant to time series forecasting.
• Experience with hyperparameter optimization using libraries like Optuna or Hyperopt.
• Strong skills in understanding and evaluating model performance using metrics like MSE, RMSE, MAE, MAPE, and R-squared.
• Familiarity with backtesting functionalities for validating model performance.
• Experience in model deployment, including serialisation and productionising models for real-time data streams.
• Proficiency in using Git for version control and collaboration.

4. Practical experience with different team management methods and frameworks.

5. Solid knowledge of the software development life cycle processes and procedures.

6. Knowledge of project documentation principles.

General:

• Bachelor's degree or higher in Computer Science, Information Technology or a related field.
• Strong problem-solving skills, with the ability to anticipate risks and difficulties in advance.
• High level of self-organization and time management.
• Attentiveness and attention to detail.
• Excellent communication and reporting skills, with the ability to convey complex information concisely and effectively.
• Ability to build long-term relationships with team members.
• Good command of spoken and written English.

What We Offer:

• At DataObrii, we offer competitive wages that reflect your expertise and commitment, ensuring that your efforts are valued and appreciated.
• We provide the flexibility to work from anywhere. Work from the comfort of your home while staying connected with a collaborative and supportive team.
• You will lead and manage projects that challenge your skills and expand your knowledge. 

About DataObrii

DataObrii is a young company, which is dealing with the development of computational systems for machine learning and big data analysis.

Our focus is on real-world problems and real-world solutions. The keys to our success are our focus on continuous improvement of our employees and our company, our dedication to keeping up with current and emerging technologies, and our commitment to delivering complete solutions.

Company website:

dataobrii.com

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.

In Competera, we are building a place where optimal pricing decisions can be made easily. We believe that AI technologies will soon drive all challenging decisions and are capable of helping humans be better. We are now looking for a Middle Data Scientist to change the way we deliver our solution to customers.
 

You could be a perfect match for the position if

You want to:

• Validate datasets to ensure data accuracy and consistency.
• Design proof-of-concept (POC) solutions to explore new approaches.
• Develop technical solutions by mapping requirements to existing tools and functionalities.
• Train models and create custom approaches for new domains.
• Troubleshoot data processing and model performance issues.

You have:

• 2+ years of experience in data science or a related field.
• Strong SQL skills for data manipulation and extraction.
• Proficiency in Python, with the ability to write modular and readable code for experiments and prototypes.
• A solid mathematical background, preferably in a Computer Science-related field.
• Expertise in scientific Python libraries, including NumPy, pandas, scikit-learn, and either Keras/TensorFlow or PyTorch.
• Familiarity with Time Series Forecasting methodologies.
• Experience in statistical testing, including A/B testing.
• 1+ years working with tabular and multimodal data (e.g., combining tabular data with text, audio, or images).
• Upper-intermediate or higher English level.

Soft skills:

• Analytical mindset and critical thinking to solve complex problems.
• Agile approach, with the ability to experiment and test hypotheses in a dynamic business environment.
• Business-oriented thinking, capable of translating complex models into clear business insights.
• Curiosity and a drive for continuous learning in the data domain.
• Strong team player, able to collaborate across cross-functional teams.

You’re gonna love it, and here’s why:

• Rich innovative software stack, freedom to choose the best suitable technologies.
• Remote-first ideology: freedom to operate from the home office or any suitable coworking.
• Flexible working hours (we start from 8 to 11 am) and no time tracking systems on.
• Regular performance and compensation reviews.
• Recurrent 1-1s and measurable OKRs.
• In-depth onboarding with a clear success track.
• Competera covers 70% of your training/course fee.
• 20 vacation days, 15 days off, and up to one week of paid Christmas holidays.
• 20 business days of sick leave.
• Partial medical insurance coverage.
• We reimburse the cost of coworking.

Drive innovations with us. Be a Competerian.

We are looking for a passionate Senior Machine Learning Engineer eager to drive innovation and excellence in our machine learning processes. We strongly prefer those well-versed in the financial sector.

Join us to be part of a forward-thinking team that values innovation, growth, and collaboration.

Responsibilities:

• Cross-Functional Collaboration: Work closely with cross-functional teams to implement and support cutting-edge ML models
• Data-Driven Research: Conduct research and experiments with diverse datasets to optimize ML model performance
• Workflow Management: Handle complex data workflows with ease and efficiency
• Expert Knowledge Development: Deepen your expertise in your chosen field, staying ahead of industry trends
• Process Improvement: Enhance end-to-end development processes and pipelines, including data collection tools and production deployment, with a focus on CI/CD
• Continuous Learning: Stay at the forefront of technological advancements and trends in data science and AI
• Mentorship: Support and mentor junior team members, fostering a culture of knowledge sharing and growth
   

Requirements:

• Experience: 5+ years in machine learning and MLOps, with a track record of delivering impactful AI/ML solutions
• Research & Experimentation: Proven ability to conduct research and experiments to enhance AI/ML model performance
• Project Lifecycle Management: Skilled in handling all project stages, from business analysis to product implementation
• Python Proficiency: Expert in Python for crafting robust and high-quality code; experience with version control systems (preferably Git)
• Database Expertise: Proficient in working with databases and SQL (e.g., MS SQL, Snowflake)
• AWS Mastery: Hands-on experience with AWS cloud platform (e.g., SageMaker, Step Functions, Glue, Lambda, SQS, ECS, S3, ECR, CloudWatch, IAM, MWAA)
• Container & Orchestration Tools: Deep understanding of containers and orchestration tools (e.g., Docker, CI/CD)
• Remote Work Savvy: Comfortable working remotely and effectively communicating with cross-functional teams
• Financial Acumen: Strong foundational understanding of financial markets
• Language Proficiency: English proficiency at B2 level or higher is mandatory

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.

The Product Data Science team at Noom (www.noom.com) is seeking a mid-level Data Scientist Contractor. The primary responsibility is to conduct product analysis and help design & evaluate A/B tests.

Noom is more than just a health-tech company — it's a mission-driven organization that has helped over 50 million users worldwide build healthier habits through science-backed behavioral psychology. Backed by $650M+ in funding and recognized by Forbes as one of America's Best Startup Employers, Noom is scaling rapidly. If you're looking to work on a product that genuinely changes lives — this is the place.
 

The Product Data Science team currently consists of 4 other Data Scientists, who work together to tackle a variety of projects each week. We sit alongside the Business Data Science team (also 4 people) and the BI Engineering team.
 

“Product” at Noom covers all their in-app programs and features (including Noom Med!), as well as our Growth efforts (i.e. how we position and price our different product offerings!). 
 

Key Responsibilities:

• Product Analysis:

  - Answer insightful analysis questions from stakeholders across the Product org

  - Be able to ramp up on how different parts of the product & our data model function, to pull accurate results

  - Partner with PMs and Engineers to design key metrics for different initiatives

• Experiment Analysis:

  - Be the “stats expert” alongside PMs to ensure we design effective experiments

  - Understand and be able to intuitively explain concepts like power & sample size

  - Analyze experiment results to determine what is statistically significant, being able to take into account common pitfalls and “p-hacking” that can happen with A/B testing

• Specific Deliverables (First 3-6 months):

  - Ramp up on a particular product area and start answering ad hoc insight questions from there

  - Design an experiment (with another Product DS there to mentor), see it launch, and then analyze it

  - Give feedback on new team processes and come up with an idea to iterate/make a new one
   

Requirements:

• Strong proficiency in SQL and a solid understanding of data modeling concepts
• Proficiency with Python, ideally data analysis/science packages like Pandas and Stats
• Good “Data storytelling” and stakeholder communication: can explain technical concepts in an intuitive way
• Detail-oriented: can sense-check your output and correct errors before sharing results with stakeholders

• A good product-sense and familiarity with fundamental “product” metrics (like DAU, retention, etc)

   

What We Offer:

• Strong goal-oriented team, and a research mindset
• Opportunity to leverage your engineering skills for fellow engineers and shape the future of AI
• Working with the newest technical equipment
• 20 working days of annual vacation leave
• English courses, Educational Events & Conferences

• Medical insurance

   

About you:

We are hiring an experienced Machine Learning Engineer to join our team. This specialist will be responsible for refactoring our ML codebase, integrating new infrastructure, and developing reusable modules. Working closely with our data science and engineering teams, the Machine Learning Engineer will play a key role in enhancing the maintainability, scalability, and performance of our ML systems.

About project:

Join our client’s innovative team, working at the forefront of agricultural technology. They are dedicated to developing cutting-edge solutions that combine IoT and AI to optimize processes in smart agriculture. The core objective of this project is to monitor and improve crucial natural processes, thereby enhancing efficiency and sustainability in the agricultural sector.

Our client’s ML infrastructure processes data from IoT sensors placed in beehives to monitor temperature, humidity, and other environmental factors. This data is used to create predictive models focused on colony health, queen problems, and pollination efficiency. By leveraging real-time data and advanced technologies, the platform helps to drive better outcomes for food production and biodiversity, making a tangible impact on global food systems. The team is looking for someone who can help improve the underlying architecture of these systems while maintaining their functionality and accuracy.

Your area of responsibility:

• Restructuring and optimizing existing Machine Learning code to enhance its readability, ease of maintenance, and performance, all while ensuring core functionality is preserved.
• Integrating ML models and their associated pipelines with recently developed infrastructure elements to guarantee smooth operation and compatibility.
• Designing and implementing reusable Machine Learning modules intended for common tasks such as preparing data, engineering features, and training or evaluating models.
• Developing and deploying both unit and integration tests to uphold code quality standards and confirm reliability.
• Identifying and putting into practice improvements aimed at boosting model performance, increasing efficiency, and supporting scalability.
• Collaborating effectively with colleagues who are not located in the same place, offering guidance and participating in code review processes to receive feedback.

Skills and requirements:

• A minimum of 5 years’ professional experience in software engineering, with a strong focus on Machine Learning systems.
• Demonstrated high proficiency in Python and essential ML libraries (such as TensorFlow, PyTorch, and scikit-learn).
• A proven history of successfully refactoring complex existing codebases without compromising original functionality.
• Experience in the design and deployment of software components and libraries intended for reuse.
• Familiarity with standard ML pipelines, including processes for handling and deploying data.
• Knowledge of fundamental software engineering practices, such as managing versions, testing code, and creating documentation.
• Experience working with systems that are distributed and software stacks that are cloud-based.
• Strong capabilities in solving problems, with a focus on creating solutions that are practical and easy to maintain over time.

Will be a plus:

• Practical experience with MLOps tools and common practices in that field.
• Understanding and experience with technologies used for containerization and orchestration (like Docker or Airflow).
• Familiarity with continuous integration/continuous deployment (CI/CD) pipelines specifically for ML systems.
• Experience using tools designed for data versioning.
• Exposure to frameworks used for processing data on a large scale.
• Experience working effectively with teams that are geographically dispersed and in roles such as consulting or contract work.

We offer:

- Висококласні робочі умови: спільнота першокласних інженерів, близько 90% нашої команди це Middle та Senior; цікаві та довгострокові проєкти у різних сферах; можливість змінити проєкт в разі необхідності;

- Конкурентна ринкова компенсація в валюті (не в гривневому еквіваленті), яка виплачується без затримок;

- Власний план розвитку та регулярні перегляди компенсації;

- Оплачувані відпустки (20 днів) та лікарняні дні (5 днів);

- Всі державні свята за Українським законодавством є вихідними;

- Можливість працювати з будь-якою точки світу — ми знайдемо юридичний варіант, допоможемо легалізуватися або проконсультуємо з цього питання.

- Бухгалтерський супровід;

- Юридична підтримка в межах України;

- Повноцінна HR-підтримка та турбота.

Our client is a leading SaaS company offering pricing optimization solutions for e-commerce businesses. Its advanced technology utilizes big data, machine learning, and AI to assist customers in optimizing their pricing strategies and maximizing their profits.

About the Role:
As a Data Scientist you’ll play a critical role in shaping and enhancing our AI-driven pricing platform.

Key Responsibilities:

• Develop and Optimize Advanced ML Models: Build, improve, and deploy machine learning and statistical models for forecasting demand, analyzing price elasticities, and recommending optimal pricing strategies.
• Lead End-to-End Data Science Projects: Own your projects fully, from conceptualization and experimentation through production deployment, monitoring, and iterative improvement.
• Innovate with Generative and Predictive AI Solutions: Leverage state-of-the-art generative and predictive modeling techniques to automate complex pricing scenarios and adapt to rapidly changing market dynamics.

Required Competence and Skills:

• A Master’s or PhD in Computer Science, Physics, Applied Mathematics or a related field, demonstrating a strong foundation in analytical thinking.
• At least 5 years of professional experience in end-to-end machine learning lifecycle (design, development, deployment, and monitoring).
• At least 5 years of professional experience with Python development, including OOP, writing production-grade code, testing, and optimization.
• At least 5 years of experience with data mining, statistical analysis, and effective data visualization techniques.
• Deep familiarity with modern ML/DL methods and frameworks (e.g., PyTorch, XGBoost, scikit-learn, statsmodels).
• Strong analytical skills combined with practical experience interpreting model outputs to drive business decisions.

Nice-to-Haves:

• Practical knowledge of SQL and experience with large-scale data systems like Hadoop or Spark.
• Familiarity with MLOps tools and practices (CI/CD, model monitoring, data version control).
• Experience in reinforcement learning and Monte-Carlo methods.
• A solid grasp of microeconomic principles, including supply and demand dynamics, price elasticity, as well as econometrics.
• Experience with cloud services and platforms, preferably AWS.

Why Us?

We provide 20 days of vacation leave per calendar year (plus official national holidays of a country you are based in).

We provide full accounting and legal support in all countries we operate.

We utilize a fully remote work model with a powerful workstation and co-working space in case you need it.

We offer a highly competitive package with yearly performance and compensation reviews.

Strong background in data science from retail or logistics. 

Must-Have Skills
• Proficient in Python, including libraries such as:
• pandas, numpy, scikit-learn
• FastAPI, SQLAlchemy

Nice to Have
• Experience with agent frameworks (e.g., LangChain, Haystack, Prompt Flow)
• Hands-on experience with, or strong interest in learning, deployment and orchestration of agent-based systems
• Familiarity with Vector Databases (e.g., Qdrant)
• Experience with Graph Databases (e.g., Neo4j)
• Knowledge of Streamlit for building data apps

As a Senior Data Scientist, you will play a pivotal role in enhancing PDF Expert’s data-driven capabilities by developing predictive models and actionable insights. You will be responsible for designing and implementing data science solutions that improve product performance, user engagement, and business outcomes. You will work closely with product, marketing, and engineering teams to translate complex data into strategic decisions and ensure seamless integration of data insights into the product.

What will you do:

• Transform large data sets, analyze trends, and generate actionable insights to optimize product strategies, user acquisition, and design improvements.
• Build, test, and deploy statistical and predictive models to support product and marketing initiatives, including churn prediction and customer segmentation.
• Set up intelligent alert systems and dashboards to monitor key metrics and detect anomalies, ensuring proactive issue resolution.
• Conduct in-depth analysis to understand customer behavior, segment users based on value and usage, and develop targeted strategies for retention and conversion.
• Develop and maintain regular reports and visual dashboards, clearly communicating data-driven insights to support strategic decision-making.
• Partner with product, marketing, and engineering teams to integrate data insights into product development, marketing campaigns, and performance optimization.
• Build forecasting models to predict growth, revenue impact, and product adoption, contributing to data-driven planning and strategy.

About you:

• At least 5 years of experience as a Data Scientist working with products.
• Proficiency in Python for data analysis, modeling, and automation.
• Strong understanding of statistical methods and their application in data interpretation and model building.
• Hands-on experience building and deploying machine learning models, including churn prediction, LTV estimation, and clustering.
• Skilled in developing and maintaining data pipelines and integrating machine learning models into production.
• Experience working with at least one BI tool, such as Power BI or Tableau, for data visualization and reporting.
• Familiarity with big data technologies like Google Big Query, Snowflake, or Amazon Redshift.
• A collaborative mindset, comfortable working with product, marketing, and engineering teams.
• Ability to independently manage tasks and initiatives, driving projects to completion.

Would be a plus:

• Familiarity with marketing analytics and the ability to analyze campaign performance and customer segmentation.
• Experience with Google BigQuery for data processing and analysis.
• Expertise in designing, conducting, and interpreting A/B tests to inform product decisions.

FAVBET Tech develops software that is used by millions of players around the world for the international company FAVBET Entertainment.
We develop innovations in the field of gambling and betting through a complex multi-component platform which is capable to withstand enormous loads and provide a unique experience for players.

 

About the Role:

We are looking for a Data Scientist to join our growing team. In this role, you will work closely with the marketing, product, and engineering teams to deliver data-driven insights and build end-to-end machine learning solutions that support strategic decisions and product enhancements.

Responsibilities:

• Work on one of the following projects: User segmentation, Lifetime Value (LTV) prediction, Churn prediction.
• Collaborate with marketing and product teams to understand business needs and deliver data-driven solutions.
• Analyze large-scale datasets to uncover actionable insights that drive business and product outcomes.
• Build, validate, and deploy machine learning models to solve real-world problems.
• Partner with engineering teams to ensure access to reliable data sources and develop robust feature pipelines.
• Design and conduct A/B tests to measure the impact of new features and changes.
• Present analytical findings and model results clearly to business stakeholders.

Required Qualifications:

• Minimum of 2 years of experience as a Data Scientist or ML Engineer.
• Proficiency in Python, including libraries such as sklearn, lightgbm, keras/pytorch/jax.
• Proficiency in SQL, including writing complex queries.
• Hands-on experience designing, running, and interpreting A/B tests.
• Experience with version control systems such as GitHub, GitLab, or Bitbucket.

Nice to Have:

• Experience with cloud data platforms, ideally AWS.
• Familiarity with Docker or other containerization tools.
• Understanding of MLOps fundamentals and best practices.

We offer:

• 30 days off — we value rest and recreation.
• Medical insurance for employees and the possibility of training employees at the expense of the company and gym membership.
• Remote work or the opportunity — our own modern lofty office with spacious workplace, and brand-new work equipment (near Pochaina metro station).
• Flexible work schedule — we expect a full-time commitment but do not track your working hours.
• Flat hierarchy without micromanagement — our doors are open, and all teammates are approachable.

About project

Provectus helps companies adopt ML/AI to transform the ways they operate, compete, and drive value. The focus of the company is on building ML Infrastructure to drive end-to-end AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organization-wide in such industries as Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, Manufacturing, and Internet businesses.

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
• Machine Learning & LLM Expertise
• AWS Cloud Expertise
• Technical Execution
• Team Development & Communication
   

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.