Data Science UA

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's mission is to reduce the time and money enterprises spend on state-of-the-art technology by 99%. It is the core constraint that drives the product philosophy. It forces the company to reject incremental improvements and pursue fundamental breakthroughs. These principles are the operating system for how the company thinks, builds, and ships. They are how the company turns radical ambition into reality.

About the role:
We are looking for a Full Stack AI Engineer who will join the team. You'll be an architect of the revolution against enterprise tech waste. You'll build the core platform and intelligent agents that power the company's mission — not optimizing existing workflows, but eliminating them entirely.

Requirements:
- 5+ years of industry experience in product-centric full-stack engineering roles;
- Very strong software engineering background with deep expertise in Python/Typescript.
- Hands-on LLM product patterns (prompting, tool use, routing, evals, regression testing);
Experience of working with Agents & LLMs:
- LangGraph/LangChain (know its limitations & trade-offs);
- Multi-provider routing, prompt tooling, trace/eval discipline (LangSmith);

Experience of working with Knowledge & Search Technologies:
- Vector — pgvector on PostgreSQL (semantic);
- Graph traversal — Cypher on Neo4j (relationships & enterprise context graph);
- Keyword/BM25 — lexical precision;
- Cross-Encoder (BGE Reranker) + RRF (blend lists robustly);
Deep knowledge of working with Data & Databases:
- PostgreSQL (Cloud SQL) — primary OLTP;
- SQLAlchemy and BigQuery — analytics/outcomes & cost/waste telemetry;
- Redis (Memorystore) — caching + lightweight queue/broker;
- GCS — object storage (files, audio, artifacts);

Responsibilities:
Design & Build Autonomous Agents:
- Tackle the end-to-end challenge of creating agents that solve open-ended enterprise problems.
- Wrangling high-volume enterprise data, building robust evaluation frameworks.
- Mastering the interplay between LLM prompting, fine-tuning, and scalable system architecture.
- Lead Customer Conversations & Translate to Product: Work directly with customer executives to translate their most critical objectives into breakthrough product features.
- Build the "New": Own the most audacious hypotheses, like fully autonomous optimization agents that replace entire consulting engagements and obsolete the need for army-style deployments.
- Master Deep Context: Build systems that understand enterprise architecture patterns better than most architects, automatically discovering waste and optimization opportunities.
- Take single-threaded ownership of core AI product areas, with end-to-end responsibility for customer success and business outcomes.
- Double as a Forward Deployed Engineer: Work regularly onsite with customers, and actually work with the systems.
- Every customer engagement becomes R&D for the platform, turning individual pain points into generalizable breakthroughs that serve the entire customer base

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's mission is to reduce the time and money enterprises spend on state-of-the-art technology by 99%. It is the core constraint that drives the product philosophy. It forces the company to reject incremental improvements and pursue fundamental breakthroughs. These principles are the operating system for how the company thinks, builds, and ships. They are how the company turns radical ambition into reality.

About the role:
We are looking for a Full Stack AI Engineer who will join the team. You'll be an architect of the revolution against enterprise tech waste. You'll build the core platform and intelligent agents that power the company's mission — not optimizing existing workflows, but eliminating them entirely.

Requirements:
- 5+ years of industry experience in product-centric full-stack engineering roles;
- Very strong software engineering background with deep expertise in Python/Typescript.
- Hands-on LLM product patterns (prompting, tool use, routing, evals, regression testing);
Experience of working with Agents & LLMs:
- LangGraph/LangChain (know its limitations & trade-offs);
- Multi-provider routing, prompt tooling, trace/eval discipline (LangSmith);

Experience of working with Knowledge & Search Technologies:
- Vector — pgvector on PostgreSQL (semantic);
- Graph traversal — Cypher on Neo4j (relationships & enterprise context graph);
- Keyword/BM25 — lexical precision;
- Cross-Encoder (BGE Reranker) + RRF (blend lists robustly);
Deep knowledge of working with Data & Databases:
- PostgreSQL (Cloud SQL) — primary OLTP;
- SQLAlchemy and BigQuery — analytics/outcomes & cost/waste telemetry;
- Redis (Memorystore) — caching + lightweight queue/broker;
- GCS — object storage (files, audio, artifacts);

Responsibilities:
Design & Build Autonomous Agents:
- Tackle the end-to-end challenge of creating agents that solve open-ended enterprise problems.
- Wrangling high-volume enterprise data, building robust evaluation frameworks.
- Mastering the interplay between LLM prompting, fine-tuning, and scalable system architecture.
- Lead Customer Conversations & Translate to Product: Work directly with customer executives to translate their most critical objectives into breakthrough product features.
- Build the "New": Own the most audacious hypotheses, like fully autonomous optimization agents that replace entire consulting engagements and obsolete the need for army-style deployments.
- Master Deep Context: Build systems that understand enterprise architecture patterns better than most architects, automatically discovering waste and optimization opportunities.
- Take single-threaded ownership of core AI product areas, with end-to-end responsibility for customer success and business outcomes.
- Double as a Forward Deployed Engineer: Work regularly onsite with customers, and actually work with the systems.
- Every customer engagement becomes R&D for the platform, turning individual pain points into generalizable breakthroughs that serve the entire customer base

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's mission is to reduce the time and money enterprises spend on state-of-the-art technology by 99%. It is the core constraint that drives the product philosophy. It forces the company to reject incremental improvements and pursue fundamental breakthroughs. These principles are the operating system for how the company thinks, builds, and ships. They are how the company turns radical ambition into reality.

About the role:
We are looking for a Full Stack AI Engineer who will join the team. You'll be an architect of the revolution against enterprise tech waste. You'll build the core platform and intelligent agents that power the company's mission — not optimizing existing workflows, but eliminating them entirely.

Requirements:
- 5+ years of industry experience in product-centric full-stack engineering roles;
- Very strong software engineering background with deep expertise in Python/Typescript.
- Hands-on LLM product patterns (prompting, tool use, routing, evals, regression testing);
Experience of working with Agents & LLMs:
- LangGraph/LangChain (know its limitations & trade-offs);
- Multi-provider routing, prompt tooling, trace/eval discipline (LangSmith);

Experience of working with Knowledge & Search Technologies:
- Vector — pgvector on PostgreSQL (semantic);
- Graph traversal — Cypher on Neo4j (relationships & enterprise context graph);
- Keyword/BM25 — lexical precision;
- Cross-Encoder (BGE Reranker) + RRF (blend lists robustly);
Deep knowledge of working with Data & Databases:
- PostgreSQL (Cloud SQL) — primary OLTP;
- SQLAlchemy and BigQuery — analytics/outcomes & cost/waste telemetry;
- Redis (Memorystore) — caching + lightweight queue/broker;
- GCS — object storage (files, audio, artifacts);

Responsibilities:
Design & Build Autonomous Agents:
- Tackle the end-to-end challenge of creating agents that solve open-ended enterprise problems.
- Wrangling high-volume enterprise data, building robust evaluation frameworks.
- Mastering the interplay between LLM prompting, fine-tuning, and scalable system architecture.
- Lead Customer Conversations & Translate to Product: Work directly with customer executives to translate their most critical objectives into breakthrough product features.
- Build the "New": Own the most audacious hypotheses, like fully autonomous optimization agents that replace entire consulting engagements and obsolete the need for army-style deployments.
- Master Deep Context: Build systems that understand enterprise architecture patterns better than most architects, automatically discovering waste and optimization opportunities.
- Take single-threaded ownership of core AI product areas, with end-to-end responsibility for customer success and business outcomes.
- Double as a Forward Deployed Engineer: Work regularly onsite with customers, and actually work with the systems.
- Every customer engagement becomes R&D for the platform, turning individual pain points into generalizable breakthroughs that serve the entire customer base

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's mission is to reduce the time and money enterprises spend on state-of-the-art technology by 99%. It is the core constraint that drives the product philosophy. It forces the company to reject incremental improvements and pursue fundamental breakthroughs. These principles are the operating system for how the company thinks, builds, and ships. They are how the company turns radical ambition into reality.

About the role:
We are looking for a Full Stack AI Engineer who will join the team. You'll be an architect of the revolution against enterprise tech waste. You'll build the core platform and intelligent agents that power the company's mission — not optimizing existing workflows, but eliminating them entirely.

Requirements:
- 5+ years of industry experience in product-centric full-stack engineering roles;
- Very strong software engineering background with deep expertise in Python/Typescript.
- Hands-on LLM product patterns (prompting, tool use, routing, evals, regression testing);
Experience of working with Agents & LLMs:
- LangGraph/LangChain (know its limitations & trade-offs);
- Multi-provider routing, prompt tooling, trace/eval discipline (LangSmith);

Experience of working with Knowledge & Search Technologies:
- Vector — pgvector on PostgreSQL (semantic);
- Graph traversal — Cypher on Neo4j (relationships & enterprise context graph);
- Keyword/BM25 — lexical precision;
- Cross-Encoder (BGE Reranker) + RRF (blend lists robustly);
Deep knowledge of working with Data & Databases:
- PostgreSQL (Cloud SQL) — primary OLTP;
- SQLAlchemy and BigQuery — analytics/outcomes & cost/waste telemetry;
- Redis (Memorystore) — caching + lightweight queue/broker;
- GCS — object storage (files, audio, artifacts);

Responsibilities:
Design & Build Autonomous Agents:
- Tackle the end-to-end challenge of creating agents that solve open-ended enterprise problems.
- Wrangling high-volume enterprise data, building robust evaluation frameworks.
- Mastering the interplay between LLM prompting, fine-tuning, and scalable system architecture.
- Lead Customer Conversations & Translate to Product: Work directly with customer executives to translate their most critical objectives into breakthrough product features.
- Build the "New": Own the most audacious hypotheses, like fully autonomous optimization agents that replace entire consulting engagements and obsolete the need for army-style deployments.
- Master Deep Context: Build systems that understand enterprise architecture patterns better than most architects, automatically discovering waste and optimization opportunities.
- Take single-threaded ownership of core AI product areas, with end-to-end responsibility for customer success and business outcomes.
- Double as a Forward Deployed Engineer: Work regularly onsite with customers, and actually work with the systems.
- Every customer engagement becomes R&D for the platform, turning individual pain points into generalizable breakthroughs that serve the entire customer base

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 the fast-moving remote team building AI-driven financial tools for the U.S. auto industry.
The product is oriented on the B2B segment, specifically on Sales and Marketing Managers in the US Automotive niche. The goal of the product is to eliminate existing data lack, providing a modern UI/UX experience.

About the role:
We are looking for a Full-Stack Engineer, who will join the team.

Requirements:
- 6+ years of experience in software engineering with a strong focus and 4+ years on Node/Next/Nest/Mongo/Service Architecture backend development.
- Solid knowledge of JavaScript/TypeScript and frameworks (React is a must, near pixel-perfect layout), Elastic UI Framework (replaced with Microsoft Fluent UI);
- Understanding of CI/CD pipelines and cloud services (AWS preferred).
- Knowledge of Tools & Processes: Jira/Confluence/Slack/Cursos;
- Clear and confident English communication skills (B2+ level).
- Proactive mindset, problem-solving attitude, and ability to work autonomously.
- Playwright usage for end-to-end tests.

Responsibilities:
- Build and maintain user-facing features with high performance and responsiveness.
- Collaborate with the product manager, QA engineers, and designers to deliver intuitive, impactful functionality.
- Contribute to architectural decisions and ensure clean, maintainable code across the stack.
- Optimize the app for maximum speed, performance, and scalability.
- Participate in code reviews, live coding sessions, and technical planning.
- Work independently and drive solutions end-to-end with minimal supervision.

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's mission is to reduce the time and money enterprises spend on state-of-the-art technology by 99%. It is the core constraint that drives the product philosophy. It forces the company to reject incremental improvements and pursue fundamental breakthroughs. These principles are the operating system for how the company thinks, builds, and ships. They are how the company turns radical ambition into reality.

About the role:
We are looking for a Full Stack AI Engineer who will join the team. You'll be an architect of the revolution against enterprise tech waste. You'll build the core platform and intelligent agents that power the company's mission — not optimizing existing workflows, but eliminating them entirely.

Requirements:
- 5+ years of industry experience in product-centric full-stack engineering roles;
- Very strong software engineering background with deep expertise in Python/Typescript.
- Hands-on LLM product patterns (prompting, tool use, routing, evals, regression testing);
Experience of working with Agents & LLMs:
- LangGraph/LangChain (know its limitations & trade-offs);
- Multi-provider routing, prompt tooling, trace/eval discipline (LangSmith);

Experience of working with Knowledge & Search Technologies:
- Vector — pgvector on PostgreSQL (semantic);
- Graph traversal — Cypher on Neo4j (relationships & enterprise context graph);
- Keyword/BM25 — lexical precision;
- Cross-Encoder (BGE Reranker) + RRF (blend lists robustly);
Deep knowledge of working with Data & Databases:
- PostgreSQL (Cloud SQL) — primary OLTP;
- SQLAlchemy and BigQuery — analytics/outcomes & cost/waste telemetry;
- Redis (Memorystore) — caching + lightweight queue/broker;
- GCS — object storage (files, audio, artifacts);

Responsibilities:
Design & Build Autonomous Agents:
- Tackle the end-to-end challenge of creating agents that solve open-ended enterprise problems.
- Wrangling high-volume enterprise data, building robust evaluation frameworks.
- Mastering the interplay between LLM prompting, fine-tuning, and scalable system architecture.
- Lead Customer Conversations & Translate to Product: Work directly with customer executives to translate their most critical objectives into breakthrough product features.
- Build the "New": Own the most audacious hypotheses, like fully autonomous optimization agents that replace entire consulting engagements and obsolete the need for army-style deployments.
- Master Deep Context: Build systems that understand enterprise architecture patterns better than most architects, automatically discovering waste and optimization opportunities.
- Take single-threaded ownership of core AI product areas, with end-to-end responsibility for customer success and business outcomes.
- Double as a Forward Deployed Engineer: Work regularly onsite with customers, and actually work with the systems.
- Every customer engagement becomes R&D for the platform, turning individual pain points into generalizable breakthroughs that serve the entire customer base

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's mission is to reduce the time and money enterprises spend on state-of-the-art technology by 99%. It is the core constraint that drives the product philosophy. It forces the company to reject incremental improvements and pursue fundamental breakthroughs. These principles are the operating system for how the company thinks, builds, and ships. They are how the company turns radical ambition into reality.

About the role:
We are looking for a Full Stack AI Engineer who will join the team. You'll be an architect of the revolution against enterprise tech waste. You'll build the core platform and intelligent agents that power the company's mission — not optimizing existing workflows, but eliminating them entirely.

Requirements:
- 5+ years of industry experience in product-centric full-stack engineering roles;
- Very strong software engineering background with deep expertise in Python/Typescript.
- Hands-on LLM product patterns (prompting, tool use, routing, evals, regression testing);
Experience of working with Agents & LLMs:
- LangGraph/LangChain (know its limitations & trade-offs);
- Multi-provider routing, prompt tooling, trace/eval discipline (LangSmith);

Experience of working with Knowledge & Search Technologies:
- Vector — pgvector on PostgreSQL (semantic);
- Graph traversal — Cypher on Neo4j (relationships & enterprise context graph);
- Keyword/BM25 — lexical precision;
- Cross-Encoder (BGE Reranker) + RRF (blend lists robustly);
Deep knowledge of working with Data & Databases:
- PostgreSQL (Cloud SQL) — primary OLTP;
- SQLAlchemy and BigQuery — analytics/outcomes & cost/waste telemetry;
- Redis (Memorystore) — caching + lightweight queue/broker;
- GCS — object storage (files, audio, artifacts);

Responsibilities:
Design & Build Autonomous Agents:
- Tackle the end-to-end challenge of creating agents that solve open-ended enterprise problems.
- Wrangling high-volume enterprise data, building robust evaluation frameworks.
- Mastering the interplay between LLM prompting, fine-tuning, and scalable system architecture.
- Lead Customer Conversations & Translate to Product: Work directly with customer executives to translate their most critical objectives into breakthrough product features.
- Build the "New": Own the most audacious hypotheses, like fully autonomous optimization agents that replace entire consulting engagements and obsolete the need for army-style deployments.
- Master Deep Context: Build systems that understand enterprise architecture patterns better than most architects, automatically discovering waste and optimization opportunities.
- Take single-threaded ownership of core AI product areas, with end-to-end responsibility for customer success and business outcomes.
- Double as a Forward Deployed Engineer: Work regularly onsite with customers, and actually work with the systems.
- Every customer engagement becomes R&D for the platform, turning individual pain points into generalizable breakthroughs that serve the entire customer base

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 the fast-moving remote team building AI-driven financial tools for the U.S. auto industry.
The product is oriented on the B2B segment, specifically on Sales and Marketing Managers in the US Automotive niche. The goal of the product is to eliminate existing data lack, providing a modern UI/UX experience.

About the role:
We are looking for a Full-Stack Engineer, who will join the team.

Requirements:
- 6+ years of experience in software engineering with a strong focus and 4+ years on Node/Next/Nest/Mongo/Service Architecture backend development.
- Solid knowledge of JavaScript/TypeScript and frameworks (React is a must, near pixel-perfect layout), Elastic UI Framework (replaced with Microsoft Fluent UI);
- Understanding of CI/CD pipelines and cloud services (AWS preferred).
- Knowledge of Tools & Processes: Jira/Confluence/Slack/Cursos;
- Clear and confident English communication skills (B2+ level).
- Proactive mindset, problem-solving attitude, and ability to work autonomously.
- Playwright usage for end-to-end tests.

Responsibilities:
- Build and maintain user-facing features with high performance and responsiveness.
- Collaborate with the product manager, QA engineers, and designers to deliver intuitive, impactful functionality.
- Contribute to architectural decisions and ensure clean, maintainable code across the stack.
- Optimize the app for maximum speed, performance, and scalability.
- Participate in code reviews, live coding sessions, and technical planning.
- Work independently and drive solutions end-to-end with minimal supervision.

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's mission is to reduce the time and money enterprises spend on state-of-the-art technology by 99%. It is the core constraint that drives the product philosophy. It forces the company to reject incremental improvements and pursue fundamental breakthroughs. These principles are the operating system for how the company thinks, builds, and ships. They are how the company turns radical ambition into reality.

About the role:
We are looking for a Full Stack AI Engineer who will join the team. You'll be an architect of the revolution against enterprise tech waste. You'll build the core platform and intelligent agents that power the company's mission — not optimizing existing workflows, but eliminating them entirely.

Requirements:
- 5+ years of industry experience in product-centric full-stack engineering roles;
- Very strong software engineering background with deep expertise in Python/Typescript.
- Hands-on LLM product patterns (prompting, tool use, routing, evals, regression testing);
Experience of working with Agents & LLMs:
- LangGraph/LangChain (know its limitations & trade-offs);
- Multi-provider routing, prompt tooling, trace/eval discipline (LangSmith);

Experience of working with Knowledge & Search Technologies:
- Vector — pgvector on PostgreSQL (semantic);
- Graph traversal — Cypher on Neo4j (relationships & enterprise context graph);
- Keyword/BM25 — lexical precision;
- Cross-Encoder (BGE Reranker) + RRF (blend lists robustly);
Deep knowledge of working with Data & Databases:
- PostgreSQL (Cloud SQL) — primary OLTP;
- SQLAlchemy and BigQuery — analytics/outcomes & cost/waste telemetry;
- Redis (Memorystore) — caching + lightweight queue/broker;
- GCS — object storage (files, audio, artifacts);

Responsibilities:
Design & Build Autonomous Agents:
- Tackle the end-to-end challenge of creating agents that solve open-ended enterprise problems.
- Wrangling high-volume enterprise data, building robust evaluation frameworks.
- Mastering the interplay between LLM prompting, fine-tuning, and scalable system architecture.
- Lead Customer Conversations & Translate to Product: Work directly with customer executives to translate their most critical objectives into breakthrough product features.
- Build the "New": Own the most audacious hypotheses, like fully autonomous optimization agents that replace entire consulting engagements and obsolete the need for army-style deployments.
- Master Deep Context: Build systems that understand enterprise architecture patterns better than most architects, automatically discovering waste and optimization opportunities.
- Take single-threaded ownership of core AI product areas, with end-to-end responsibility for customer success and business outcomes.
- Double as a Forward Deployed Engineer: Work regularly onsite with customers, and actually work with the systems.
- Every customer engagement becomes R&D for the platform, turning individual pain points into generalizable breakthroughs that serve the entire customer base

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's mission is to reduce the time and money enterprises spend on state-of-the-art technology by 99%. It is the core constraint that drives the product philosophy. It forces the company to reject incremental improvements and pursue fundamental breakthroughs. These principles are the operating system for how the company thinks, builds, and ships. They are how the company turns radical ambition into reality.

About the role:
We are looking for a Full Stack AI Engineer who will join the team. You'll be an architect of the revolution against enterprise tech waste. You'll build the core platform and intelligent agents that power the company's mission — not optimizing existing workflows, but eliminating them entirely.

Requirements:
- 5+ years of industry experience in product-centric full-stack engineering roles;
- Very strong software engineering background with deep expertise in Python/Typescript.
- Hands-on LLM product patterns (prompting, tool use, routing, evals, regression testing);
Experience of working with Agents & LLMs:
- LangGraph/LangChain (know its limitations & trade-offs);
- Multi-provider routing, prompt tooling, trace/eval discipline (LangSmith);

Experience of working with Knowledge & Search Technologies:
- Vector — pgvector on PostgreSQL (semantic);
- Graph traversal — Cypher on Neo4j (relationships & enterprise context graph);
- Keyword/BM25 — lexical precision;
- Cross-Encoder (BGE Reranker) + RRF (blend lists robustly);
Deep knowledge of working with Data & Databases:
- PostgreSQL (Cloud SQL) — primary OLTP;
- SQLAlchemy and BigQuery — analytics/outcomes & cost/waste telemetry;
- Redis (Memorystore) — caching + lightweight queue/broker;
- GCS — object storage (files, audio, artifacts);

Responsibilities:
Design & Build Autonomous Agents:
- Tackle the end-to-end challenge of creating agents that solve open-ended enterprise problems.
- Wrangling high-volume enterprise data, building robust evaluation frameworks.
- Mastering the interplay between LLM prompting, fine-tuning, and scalable system architecture.
- Lead Customer Conversations & Translate to Product: Work directly with customer executives to translate their most critical objectives into breakthrough product features.
- Build the "New": Own the most audacious hypotheses, like fully autonomous optimization agents that replace entire consulting engagements and obsolete the need for army-style deployments.
- Master Deep Context: Build systems that understand enterprise architecture patterns better than most architects, automatically discovering waste and optimization opportunities.
- Take single-threaded ownership of core AI product areas, with end-to-end responsibility for customer success and business outcomes.
- Double as a Forward Deployed Engineer: Work regularly onsite with customers, and actually work with the systems.
- Every customer engagement becomes R&D for the platform, turning individual pain points into generalizable breakthroughs that serve the entire customer base

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 Data Scientist / NLP Lead to spearhead the development of cutting-edge natural language processing solutions for the Ukrainian LLM project. You will lead the NLP team in designing, implementing, and deploying large-scale language models and NLP algorithms that power the products.

This role is critical to the 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.
 

Requirements:
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.
- An 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 on how to build 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 clearly.

Responsibilities:
- 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 the 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 model development.

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.

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 the largest Data Science Community in Eastern Europe, boasting a network of over 30,000 AI top engineers.

About the client:
We are working with a new generation of data service provider, specializing in data consulting and data-driven digital marketing, dedicated to transforming data into business impact across the entire value chain of organizations. The company’s data-driven services are built upon the deep AI expertise the company’s acquired with a 1000+ client base around the globe. The company has 1000 employees across 20 offices who are focused on accelerating digital transformation.

About the role:
We are seeking a Senior Product Manager to oversee the delivery of AI and data-driven solutions, ensuring alignment with business objectives and agile execution. The PM will facilitate cross-team collaboration and continuous improvement.

Required skills:
- 8+ years of experience as a Product Manager in technology projects.
- Strong knowledge of Agile Scrum methodologies.
- Proven experience managing end-to-end delivery of AI or data products.
- Excellent communication and facilitation skills.
- Ability to align technical and business stakeholders.
- Strong analytical thinking and problem-solving capabilities.

Responsibilities:
- Lead agile product development cycles.
- Facilitate communication between stakeholders and teams.
- Organize and lead Scrum ceremonies.
- Drive continuous improvement and remove impediments.
- Support in executing the product vision, strategy, and roadmap.
- Working closely with cross-functional teams to ensure the product meets client and user needs.
- Align with business objectives, and deliver value to end-users.

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 the largest Data Science Community in Eastern Europe, boasting a network of over 30,000 AI top engineers.

About the client:
We are working with a new generation of data service provider, specializing in data consulting and data-driven digital marketing, dedicated to transforming data into business impact across the entire value chain of organizations. The company’s data-driven services are built upon the deep AI expertise the company’s acquired with a 1000+ client base around the globe. The company has 1000 employees across 20 offices who are focused on accelerating digital transformation.

About the role:
We are looking for a DevOps Engineer to ensure reliable deployment, automation, and monitoring of AI/ML and cloud applications. The role involves managing CI/CD pipelines, infrastructure automation, and supporting MLOps/AIOps practices.

Required skills:
- 6+ years of experience as a DevOps Engineer or similar role in cloud environments.
- Proficiency in CI/CD tools (Jenkins, GitHub Actions) and infrastructure as code (Terraform).
- Strong hands-on experience with Kubernetes and Azure DevOps ecosystems.
- Experience in scripting with Bash and Python for automation tasks.
- Familiarity with MLOps tools such as MLflow, model monitoring, and drift detection.
- Understanding of AIOps principles for intelligent operations automation.
- Experience ensuring system reliability, observability, and performance optimization.
- Strong collaboration and documentation skills.

Responsibilities:
- Assist in integrating security practices into DevOps processes;
- Support senior engineers in implementing security tools, automating security processes, and ensuring the security of infrastructure and applications.
- Develop and maintain CI/CD pipelines (Jenkins, GitHub Actions).
- Implement infrastructure as code using Terraform and Kubernetes.
- Collaborate with data and AI teams to support MLOps workflows.
- Ensure observability, performance, and security of deployed systems.

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's mission is to reduce the time and money enterprises spend on state-of-the-art technology by 99%. It is the core constraint that drives the product philosophy. It forces the company to reject incremental improvements and pursue fundamental breakthroughs. These principles are the operating system for how the company thinks, builds, and ships. They are how the company turns radical ambition into reality.

About the role:
We are looking for a Full Stack AI Engineer who will join the team. You'll be an architect of the revolution against enterprise tech waste. You'll build the core platform and intelligent agents that power the company's mission — not optimizing existing workflows, but eliminating them entirely.

Requirements:
- 5+ years of industry experience in product-centric full-stack engineering roles;
- Very strong software engineering background with deep expertise in Python/Typescript.
- Hands-on LLM product patterns (prompting, tool use, routing, evals, regression testing);
Experience of working with Agents & LLMs:
- LangGraph/LangChain (know its limitations & trade-offs);
- Multi-provider routing, prompt tooling, trace/eval discipline (LangSmith);

Experience of working with Knowledge & Search Technologies:
- Vector — pgvector on PostgreSQL (semantic);
- Graph traversal — Cypher on Neo4j (relationships & enterprise context graph);
- Keyword/BM25 — lexical precision;
- Cross-Encoder (BGE Reranker) + RRF (blend lists robustly);
Deep knowledge of working with Data & Databases:
- PostgreSQL (Cloud SQL) — primary OLTP;
- SQLAlchemy and BigQuery — analytics/outcomes & cost/waste telemetry;
- Redis (Memorystore) — caching + lightweight queue/broker;
- GCS — object storage (files, audio, artifacts);

Responsibilities:
Design & Build Autonomous Agents:
- Tackle the end-to-end challenge of creating agents that solve open-ended enterprise problems.
- Wrangling high-volume enterprise data, building robust evaluation frameworks.
- Mastering the interplay between LLM prompting, fine-tuning, and scalable system architecture.
- Lead Customer Conversations & Translate to Product: Work directly with customer executives to translate their most critical objectives into breakthrough product features.
- Build the "New": Own the most audacious hypotheses, like fully autonomous optimization agents that replace entire consulting engagements and obsolete the need for army-style deployments.
- Master Deep Context: Build systems that understand enterprise architecture patterns better than most architects, automatically discovering waste and optimization opportunities.
- Take single-threaded ownership of core AI product areas, with end-to-end responsibility for customer success and business outcomes.
- Double as a Forward Deployed Engineer: Work regularly onsite with customers, and actually work with the systems.
- Every customer engagement becomes R&D for the platform, turning individual pain points into generalizable breakthroughs that serve the entire customer base

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's mission is to reduce the time and money enterprises spend on state-of-the-art technology by 99%. It is the core constraint that drives the product philosophy. It forces the company to reject incremental improvements and pursue fundamental breakthroughs. These principles are the operating system for how the company thinks, builds, and ships. They are how the company turns radical ambition into reality.

About the role:
We are looking for a Full Stack AI Engineer who will join the team. You'll be an architect of the revolution against enterprise tech waste. You'll build the core platform and intelligent agents that power the company's mission — not optimizing existing workflows, but eliminating them entirely.

Requirements:
- 5+ years of industry experience in product-centric full-stack engineering roles;
- Very strong software engineering background with deep expertise in Python/Typescript.
- Hands-on LLM product patterns (prompting, tool use, routing, evals, regression testing);
Experience of working with Agents & LLMs:
- LangGraph/LangChain (know its limitations & trade-offs);
- Multi-provider routing, prompt tooling, trace/eval discipline (LangSmith);

Experience of working with Knowledge & Search Technologies:
- Vector — pgvector on PostgreSQL (semantic);
- Graph traversal — Cypher on Neo4j (relationships & enterprise context graph);
- Keyword/BM25 — lexical precision;
- Cross-Encoder (BGE Reranker) + RRF (blend lists robustly);
Deep knowledge of working with Data & Databases:
- PostgreSQL (Cloud SQL) — primary OLTP;
- SQLAlchemy and BigQuery — analytics/outcomes & cost/waste telemetry;
- Redis (Memorystore) — caching + lightweight queue/broker;
- GCS — object storage (files, audio, artifacts);

Responsibilities:
Design & Build Autonomous Agents:
- Tackle the end-to-end challenge of creating agents that solve open-ended enterprise problems.
- Wrangling high-volume enterprise data, building robust evaluation frameworks.
- Mastering the interplay between LLM prompting, fine-tuning, and scalable system architecture.
- Lead Customer Conversations & Translate to Product: Work directly with customer executives to translate their most critical objectives into breakthrough product features.
- Build the "New": Own the most audacious hypotheses, like fully autonomous optimization agents that replace entire consulting engagements and obsolete the need for army-style deployments.
- Master Deep Context: Build systems that understand enterprise architecture patterns better than most architects, automatically discovering waste and optimization opportunities.
- Take single-threaded ownership of core AI product areas, with end-to-end responsibility for customer success and business outcomes.
- Double as a Forward Deployed Engineer: Work regularly onsite with customers, and actually work with the systems.
- Every customer engagement becomes R&D for the platform, turning individual pain points into generalizable breakthroughs that serve the entire customer base