What are the responsibilities and job description for the Machine Learning Engineer position at Harrison Clarke?
MLOps Engineer role | HealthTech company
We’re working with a high-calibre, AI-native healthtech company tackling one of the most complex and manual areas in healthcare - and they’re hiring an MLOps Engineer.
This isn’t a “keep the lights on” infra role. It’s about building the ML backbone from the ground up for systems that directly impact real-world healthcare workflows.
What you’d be doing:
- Designing and scaling end-to-end ML pipelines (training → deployment → monitoring)
- Owning LLMOps infrastructure (evaluation, observability, cost latency optimisation)
- Building robust, production-grade systems for unstructured healthcare data (docs, claims, clinical text)
- Working closely with applied ML / research teams to take models into real-world use
Tech environment:
Modern stack across cloud, Kubernetes, distributed systems, and LLM tooling. Heavy focus on performance, reliability, and iteration speed.
What they’re looking for:
- Strong background in ML infrastructure / platform engineering
- Experience deploying and scaling ML systems in production
- Exposure to LLMs / GenAI systems (or strong interest in moving into this space)
- Engineers who like ownership, not just implementation
Why it’s interesting:
- Highly technical, first-principles engineering problems
- Real-world impact in healthcare (not just experimentation)
- Small, sharp team — high autonomy and visibility
- Opportunity to shape how ML systems are built from day one
NYC preferred (hybrid), but open to strong candidates for remote working