Senior ML Engineering Manager — Health AI & Systems Leader

Capital Rx; Denver (CO); Hybrid; USD 174,000 - 218,000; Full time

Job summary

Judi Health, a health technology company, is hiring a Senior Machine Learning Engineering Manager to lead design and implementation of AI systems that leverage NLP, NLG, multimodal data, chatbots, and RAG-based QnA.

In this role you will guide teams, productionize ML solutions, and drive APIs, model lifecycle, and rigorous quality assurance while ensuring HIPAA compliance in a fast-paced startup environment.

Qualifications

• Bachelor's or Master's degree in CS, ML, or related quantitative field.
• 8+ years of ML-focused industry experience (4+ with Masters).
• 3+ years of engineering management leading 4+ engineers.
• Experience across the AI development lifecycle.
• Strong Python and ML library knowledge (PyTorch).
• Cloud experience (AWS or Azure).
• Familiarity with GenAI services and prompt tuning.
• Excellent communication and collaboration skills.

Responsibilities

• Lead ML projects from planning to delivery with team growth.
• Productionize ML solutions in Document understanding, Search and QnA, GenAI.
• Design and implement APIs for seamless AI model integration.
• Cover problem definition, data exploration, feature engineering, training, validation, deployment.
• Participate in code reviews, testing, and QA processes.
• Troubleshoot AI model, integration, deployment, and backend issues.
• Document system designs and architectural decisions.
• Ensure HIPAA-compliant handling of healthcare data.

Skills

Machine Learning Leadership

NLP & GenAI systems

Python

Team Management

ML model deployment

Education

Bachelor's or Master's in CS/ML

Tools

PyTorch

AWS

Azure

OpenAI GPT

Google Gemma

Job description

Judi Health, a health technology company, is hiring a Senior Machine Learning Engineering Manager to lead design and implementation of AI systems that leverage NLP, NLG, multimodal data, chatbots, and RAG-based QnA.

In this role you will guide teams, productionize ML solutions, and drive APIs, model lifecycle, and rigorous quality assurance while ensuring HIPAA compliance in a fast-paced startup environment.