Applied ML Engineer: Medical Device Certification AI

Scarlet; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

Scarlet is seeking an Applied Machine Learning engineer to own meaningful problems in how we assess medical devices: define success with domain experts, decide what to build and test, and take ML systems through deployment and measurable improvement in production.

You’ll work with clinicians, assessors and engineers to build reliable ML systems for evidence-heavy certification workflows, balancing accuracy, latency and safety in a domain with scarce precedent.

Qualifications

• Experience deploying agent systems with tool use.
• Experience building retrieval or document-understanding systems.
• Ability to work with domain experts to define success and measure outcomes.

Responsibilities

• Own ML problems from conception to production.
• Build datasets and benchmarks with expert guidance.
• Ensure source attribution and manage trade-offs between accuracy and cost.
• Collaborate with clinicians and engineers to integrate into workflows.

Skills

Deep learning

Agent systems

Information retrieval

Context management

Production deployment

Security considerations

Tools

TensorFlow

PyTorch

Job description

Scarlet is seeking an Applied Machine Learning engineer to own meaningful problems in how we assess medical devices: define success with domain experts, decide what to build and test, and take ML systems through deployment and measurable improvement in production.

You’ll work with clinicians, assessors and engineers to build reliable ML systems for evidence-heavy certification workflows, balancing accuracy, latency and safety in a domain with scarce precedent.