HealthEdge

Machine Learning Engineer

• Develop and implement AI agents and automation for internal engineering workflows and customer-facing delivery processes
• Own the full lifecycle from problem discovery through prototyping, evaluation, hardening, and production deployment
• Contribute reusable libraries, prompt templates, tool-use patterns, and evaluation scaffolding to the AI Platform
• Partner with software engineers to integrate AI into existing software infrastructure
• Work with product managers, implementation consultants, engineers, and business operations teams to identify pain points and scope solutions
• Iterate toward measurable business outcomes
• Stay current with LLMs, agentic frameworks, machine learning, and healthcare technology
• Optimize AI systems for accuracy, latency, cost, and safety, including human-in-the-loop design and healthcare guardrails
• Maintain documentation of model development processes, methodologies, and results