Remote ML Engineer — AI Agents for HealthTech

F-Prime Capital; United States; On-site; USD 110,000 - 135,000; Full time

Job summary

HealthEdge is seeking a Machine Learning Engineer to design, build, and ship AI agents and automation across Engineering, Product, and Delivery. You will partner with stakeholders to understand workflows, identify high-leverage opportunities, and deliver working solutions end-to-end.

Stay current with LLMs, agentic frameworks, and healthcare data while optimizing AI systems for accuracy, latency, cost, and safety.

Qualifications

• Master's or Bachelor's with relevant experience required.
• 2–4 years of experience building and deploying ML/AI systems in production.
• Strong Python and ML framework experience (PyTorch, scikit-learn).

Responsibilities

• AI Platform Development: Build and deploy AI Agents and automation across engineering workflows and customer-facing delivery processes.
• Integration: Collaborate with software engineers to integrate AI into existing infrastructure.
• Collaboration: Work with product managers, engineers, and operations to identify pain points and deliver measurable outcomes.
• Research and Learning: Stay current with LLMs, agentic frameworks, ML, and healthcare tech; contribute ideas for innovation.
• Performance and Reliability: Optimize AI systems for accuracy, latency, cost, and safety with human-in-the-loop guardrails.
• Documentation: Maintain clear documentation of model development processes and results.

Skills

Python

LLM APIs

LangChain

Strands

Prompt engineering

PyTorch

Scikit-learn

Communication skills

Education

Master's degree in Computer Science / ML / Data Science

Bachelor's degree with relevant experience

Tools

CI/CD practices

Version control (Git)

Testing frameworks

Job description

HealthEdge is seeking a Machine Learning Engineer to design, build, and ship AI agents and automation across Engineering, Product, and Delivery. You will partner with stakeholders to understand workflows, identify high-leverage opportunities, and deliver working solutions end-to-end.

Stay current with LLMs, agentic frameworks, and healthcare data while optimizing AI systems for accuracy, latency, cost, and safety.