Senior AI/ML Engineer

This client delivers digital and AI-driven solutions specifically for the life sciences and healthcare industries.

The company provides end-to-end engineering, informatics, and data science services. Our customer utilizes scientific and technical expertise to build scalable, secure, and compliant digital solutions.

This position requires developing and refining multi-RAG architecture for scientific and regulatory writing, focusing on modularity and quality assurance.

Core services and activities include:
• Artificial Intelligence.
• Scientific Informatics and Laboratory Informatics.
• Developing Custom Laboratory Software Solutions.
• Data Science and Engineering.
• Solution Design, such as designing data management infrastructure to support scientific research.
• Cloud Engineering, utilizing expertise in GCP and AWS.
• Developing High Performance Computing (HPC) platforms for tasks like cell image analysis and molecular docking.

We are looking for a skilled and motivated Senior AI /ML Engineer to join dynamic team.

• Interview process that respects people and their time
• Professional and open IT community
• Internal meet-ups and resources for knowledge sharing
• Time for recovery and relaxation
• Bright online and offline events
• Opportunity to become part of our internal volunteer community

• Architect scalable and reliable ML systems that can handle large volumes of data and real-time processing.
• Ensure the solutions are robust, secure, and scalable, considering performance, latency, and cost optimization.
• Conduct research and experimentation to explore new ML algorithms, techniques, and frameworks that can enhance the company's offerings.
• Contribute modular, well-tested code.
• Participate in code review, project management.
• Develop/refine advanced multi-RAG architecture for CSR generation.
• Extend Snowflake-based pipelines to a modular production-ready architecture.
• Build evaluation and QA workflows: hallucination detection, guardrails, completeness, regulatory alignment, content fidelity.

• Proficiency in Python programming and experience with Python data science frameworks
• Familiarity with common ML frameworks (e.g., PyTorch, Keras) and libraries (e.g., NumPy, scikit-learn)
• Experience with LLM agents, including tool using and reasoning, for instance, the combination of the RAG solution and code interpreter
• Experience with LLM fine-tuning
• Experience with the evaluation of LLM outputs (factual consistency, content recall, style matching)
• Experience with prompt engineering, context construction, token optimization, LLM reliability
• Experience with Document processing (.RTF, DOCX, table structures, content extraction)
• Experience with Modular pipeline design, clean APIs, CI/CD integration
• Experience in Docker
• Familiarity with scientific data systems (e.g. Dotmatics)
• Experience with Cheminformatics libraries (e.g. RDKit)
• Experience with GitHub/GitLab workflows (PRs, reviews, CI pipelines)
• Solid knowledge of machine learning and deep learning fundamentals
• Experience with transformer-based language models
• Ability to interpret and implement research ideas and algorithms
• Hands-on experience with relational SQL and NoSQL databases
• Upper-Intermediate or higher level of English proficiency
• Ability to work with external clients and strong communication skills, including presenting in webinars and conferences
• Ability to mentor team members and assist in their professional development
• Quick learner with the ability to adapt to new technologies, frameworks, and algorithms

Preferred Skills:

• Exposure to clinical study documentation (CSRs) or regulatory writing pipelines
• Familiarity with Microsoft Office Add-in development (Office.js, JavaScript/TypeScript, Office Scripts/Graph API)
• Chemistry/cheminformatics domain expertise
• Experience with agentic observability platforms (Langfuse)