[Hiring] Machine Learning Engineer @HealthEdge

Role Description

As a Machine Learning Engineer, you will design, build, and ship AI agents and automation that solve real problems across HealthEdge's engineering, product, and delivery organizations, including customer-facing operations. You'll partner directly with stakeholders across Engineering, Product, and healthcare professionals to understand their workflows, identify high-leverage opportunities, and deliver working solutions end-to-end. Your growing expertise in machine learning and agentic AI will have a direct impact on how HealthEdge builds software, delivers for customers, and operates at scale.

Key Responsibilities

• AI Platform Development: Develop and implement AI Agents and automation that accelerates internal engineering workflows and customer-facing delivery processes, owning the full lifecycle from problem discovery, through prototyping, evaluation, hardening, and production deployment.
• Contribute reusable libraries, prompt templates, tool-use patterns, and evaluation scaffolding back to the AI Platform.
• Integration: Partner with software engineers to integrate AI into the company's existing software infrastructure, supporting seamless functionality and performance.
• Collaboration: Work directly with product managers, implementation consultants, engineers, and business operations teams to identify pain points, scope solutions, and iterate toward measurable outcomes.
• Research and Learning: Stay current with advancements in LLMs, agentic frameworks, machine learning, and healthcare technology, and apply new knowledge to contribute ideas for innovation within the team.
• Performance and Reliability: Optimize AI systems for accuracy, latency, cost, and safety, with particular attention to human-in-the-loop design and guardrails appropriate for healthcare.
• Documentation: Maintain clear documentation of model development processes, methodologies, and results to ensure transparency and reproducibility.

Qualifications

• Education: Master's degree in Computer Science, Machine Learning, Data Science, or a related field. A Bachelor's degree with relevant experience will also be considered.
• Experience: 2–4 years of experience building and deploying ML or AI systems in production. Experience working directly with non-technical stakeholders or in embedded/consulting-style engineering roles is a strong plus.
• Technical Skills: Strong proficiency in Python. Experience with LLM APIs, agentic frameworks (LangChain, Strands, etc.), and prompt engineering alongside traditional ML frameworks (PyTorch, scikit-learn, etc.). Solid software engineering fundamentals — version control, testing, CI/CD, and comfort operating across the full development lifecycle.
• Healthcare Knowledge: Interest in or familiarity with healthcare data, clinical workflows, and regulatory requirements. Experience working with electronic health records (EHR) or other healthcare datasets is a plus.
• Analytical Skills: Strong problem-solving skills and the ability to work with complex datasets to derive actionable insights.
• Communication: Excellent verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Builder Mindset: Energized by turning ideas into working solutions. You balance speed with quality, thrive in ambiguous problem spaces, and pick up new domains quickly.
• Team Player: Ability to work collaboratively in a cross-functional team environment, accept feedback, and contribute to the success of the team.

Work Environment

• The employee is occasionally required to move around the office.
• Specific vision abilities required by this job include close vision, color vision, peripheral vision, depth perception, and ability to adjust focus.
• Work across multiple time zones in a hybrid or remote work environment.
• Long periods of time sitting and/or standing in front of a computer using video technology.
• May require travel dependent on company needs.

Compensation

The annual US base salary range for this position is $130,000 to $165,000. This salary range may cover multiple career levels at HealthEdge. Final compensation will be determined during the interview process and is based on a combination of factors including, but not limited to, your skills, experience, qualifications, and education.