Senior AI Engineer

Overview

In this role you will design and deliver end-to-end AI/ML solutions that power biomedical research at scale. You will work across the product and engineering teams to ship AI-powered features that improve researchers’ workflows and decision making. The position blends cutting-edge techniques with pragmatic, reliable software practices to create trustworthy, production-ready systems. You’ll contribute to a mission-driven platform that accelerates scientific breakthroughs for health. This is an opportunity to shape how biomedical professionals explore knowledge and solve real-world health challenges.

Pay / Benefits

• Competitive compensation
• Private medical and dental insurance
• Life insurance (4x salary)
• Personal development budget
• Wellbeing budget
• 25 days holiday + bank holidays + your birthday off

Responsibilities

• Design and implement ML/AI features end-to-end from ideation to deployment and monitoring
• Apply modular, testable software engineering practices (CI/CD, testing, observability) to AI systems
• Evaluate ML approaches (classical, NLP, LLM-based, agentic) to balance speed, cost, and performance
• Collaborate with product, design, and other engineers to scope work and ship user-facing AI features
• Document architectures and decisions to enable alignment and onboarding across teams
• Champion data quality, dataset versioning, evaluation, and real-world performance tracking
• Mentor junior AI engineers and cross-functional teammates to grow a high-trust, high-performance team culture
• Stay up-to-date with research and tools and translate insights into product opportunities
• Contribute to knowledge sharing through internal channels and technical talks

Key requirements

• Master’s degree in Computer Science, Electrical Engineering or related field
• 5+ years of experience building AI/ML systems in production
• Proficiency in Python and frameworks such as PyTorch, TensorFlow, or LangChain with model packaging into APIs

• Clear, structured communication
• Collaborative mindset in cross-functional teams
• Mentorship and leadership potential
• ML/AI system design and deployment
• PyTorch, TensorFlow, LangChain
• LLMs, embeddings, prompt engineering, fine-tuning

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