senior ai/ml engineer

ABOUT THE CLIENT

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.

PROJECT DETAILS

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.

YOUR TEAM

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

WHAT'S IN IT FOR YOU

• 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

RESPONSIBILITIES

• 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.

SKILLS

• 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 , JavaScript/TypeScript, Office Scripts/Graph API)
• Chemistry/cheminformatics domain expertise
• Experience with agentic observability platforms (Langfuse)

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