Machine Learning Engineer

HealthEdge

. Develop and implement AI agents and automation for internal engineering workflows and customer-facing delivery processes .

Posted 9/15/2026full-timeRemote • United StatesJuniorMid-Level💰 $0 - $135,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and implementing AI agents and automation, with a strong focus on machine learning systems and healthcare technology. Proficient in Python and familiar with LLM APIs and traditional ML frameworks, while effectively collaborating with cross-functional teams to drive measurable business outcomes.

Highest-signal resume keywords

Python ProficiencyMachine Learning System DeploymentLLM API ExperienceHealthcare Data FamiliarityCross-Functional Collaboration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningAI System DevelopmentPrompt EngineeringPyTorchScikit-learnVersion ControlCI/CDData ScienceProblem SolvingDocumentation

Soft Skills

Excellent CommunicationTeam CollaborationFeedback Acceptance

Tools & Technologies

LangChainStrandsAI Platform

Certifications & Qualifications

Master's Degree in Computer ScienceMaster's Degree in Machine LearningMaster's Degree in Data Science

Industry Keywords

Healthcare TechnologyClinical WorkflowsRegulatory Requirements

Tech Stack

Tools & technologies

PythonPyTorchScikit-Learn

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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
2–4 years of experience building and deploying ML or AI systems in production
Strong proficiency in Python
Experience with LLM APIs, agentic frameworks (LangChain, Strands, etc.), and prompt engineering
Experience with traditional ML frameworks such as PyTorch and scikit-learn
Software engineering fundamentals including version control, testing, and CI/CD
Comfort operating across the full development lifecycle
Interest in or familiarity with healthcare data, clinical workflows, and regulatory requirements
Strong problem-solving skills and ability to work with complex datasets to derive actionable insights
Excellent verbal and written communication skills and ability to explain technical concepts to non-technical stakeholders
Ability to work collaboratively in a cross-functional team environment, accept feedback, and contribute to team success
Candidates may be required to complete a pre-employment criminal background check

Benefits

Comp & perks

Remote work environment
Hybrid or remote work environment
May require travel dependent on company needs
Reasonable accommodations for individuals with disabilities
Equal opportunity employment and workforce diversity
Pre-employment criminal background check