Fullstack Senior Data Scientist

ABOUT THE ROLE
We're looking for an experienced Senior Data Scientist with deep expertise in Generative AI to lead projects building and implementing advanced LLM-based systems — including chatbots, AI agents, and RAG pipelines. This is a technical leadership role: you'll make architectural decisions, select technologies, set best practices, and mentor other engineers, while remaining hands-on across the full solution lifecycle.
You'll work closely with data engineers, product owners, and full-stack developers to deliver scalable GenAI applications for large enterprise clients, primarily in CPG, retail, and manufacturing.

WHAT YOU'LL WORK ON
Solution design and discovery
Lead discovery and solution design for GenAI use cases — translating business problems into concrete architectures covering LLM selection, RAG, fine-tuning, agents, and guardrails.
End-to-end GenAI applications
Build complete GenAI solutions covering data ingestion, retrieval layers, orchestration (LangChain, LlamaIndex, LangGraph), API and backend, and lightweight UI where needed.
RAG pipeline design
Design and implement RAG pipelines with vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks for relevance and robustness.
Model selection, prompting, and fine-tuning
Own prompting strategies, model selection, and fine-tuning (LoRA, QLoRA, SFT) for text, code, and multimodal models, including evaluation and A/B testing.
Safety and governance
Implement safety, compliance, and governance controls including input/output filters, PII handling, audit logs, and human-in-the-loop review where required.
Requirements and estimation
Gather technical requirements from stakeholders and produce reliable estimates for planned work.
Mentorship and knowledge sharing
Mentor other data scientists and engineers in GenAI patterns, code quality, and best practices. Contribute to internal libraries, templates, and reusable components.
Staying current
Track the GenAI landscape — new open and hosted models, agentic frameworks, evaluation techniques — and run targeted PoCs to validate emerging approaches.

WHAT WE LOOK FOR
6+ years in Data Science or AI engineering
Broad experience across the data science and AI stack, with a track record of delivering production systems.
4+ years of production Python for AI
Fluent in writing production-ready Python for AI and ML workloads — clean, maintainable, and deployable.
2+ years of production LLM development
Hands-on experience building and shipping LLM-based systems in production environments, not just research or prototypes.
Strong analytical and problem-solving skills
Able to break down ambiguous problems, make sound architectural decisions under uncertainty, and defend those decisions clearly.
Excellent English communication
Comfortable working directly with international clients and cross-functional teams. Able to translate technical complexity for non-technical stakeholders.

THE TEAM
You'll join a specialist Data Science and AI practice working alongside experienced consultants, ML engineers, and data engineers. The team delivers solutions for large international clients across CPG, retail, and manufacturing. There is a strong knowledge-sharing culture, with internal communities, competency centres, and structured learning programmes built into how the team operates.

COMPENSATION & BENEFITS
Rate
105 – 170 PLN per hour on a B2B contract, depending on experience.
Work model
Fully remote or office-based — your choice. Flexibility on working hours and contract form.
Workation policy
Option to work remotely from other locations for defined periods.
Onboarding
Comprehensive online onboarding programme with a dedicated buddy from day one.
Learning and development
Unlimited access to the Udemy learning platform from day one. Certificate training programmes, upskilling support, capability development programmes, competency centres, knowledge sharing sessions, community webinars, and over 110 training opportunities per year.
Career growth
Internal promotion pathways — 76% of managers were promoted internally. Cooperation with top-tier engineers and domain experts across the organisation.
Referral bonuses
Financial rewards for successful employee referrals.
Wellbeing
Activities to support health and wellbeing, with opportunities to contribute to charitable causes and environmental initiatives.
Equipment
Modern office equipment provided.
Employer recognition
Great Place to Work certified employer.