Machine Learning Engineering Manager

Judi Health is an enterprise health technology company providing a comprehensive suite of solutions for employers and health plans, including:

• Capital Rx
  , a public benefit corporation delivering full-service pharmacy benefit management (PBM) solutions to self-insured employers.
• Judi Health™, which offers full-service health benefit management solutions to employers, TPAs, and health plans.
• Judi®, the industry’s leading proprietary Enterprise Health Platform (EHP), consolidating all claim administration-related workflows in one scalable, secure platform.

Together with our clients, we’re rebuilding trust in healthcare in the U.S. and deploying the infrastructure we need for the care we deserve. To learn more, visit (Use the "Apply for this Job" box below)..

Join our mission to infuse cutting-edge AI/ML/GenAI into pharmacy benefits as a Machine Learning Engineering Manager. We are looking for an experienced software engineer with machine learning expertise to expand our AI capabilities, enabling increased productivity and magical experiences in our products and services.

In this role you will lead the design and implementation of complex AI systems leveraging ML models for NLP, NLG, multimodal data analysis, chatbots, and RAG-based QnA. We seek people who thrive in a collaborative team environment and enjoy creating practical, efficient, high-performance software that leverages Large Language Models (LLM), Multimodal Language Models (MLM), and other ML models and techniques. As a mission-oriented, high-growth startup, we want folks excited to make lasting impact toward transforming healthcare.

• Lead and oversee ML projects from planning to delivery, ensuring timely and budget-friendly completion. Conduct performance reviews, provide feedback, and support professional growth of team members.
• Manage a team and contribute to operationalizing machine learning (ML) solutions in Document understanding, Search and QnA, GenAI, Virtual Agents, etc.
• Oversee the design and implementation of APIs for seamless integration with AI models and services.
• Work across the complete lifecycle of ML model development: problem definition, data exploration, feature engineering, model training, validation, and deployment.
• Participate in code reviews, testing, and quality assurance processes.
• Troubleshoot and resolve technical issues related to AI model, integration, deployment, and backend services.
• Document and communicate development processes, system designs, and architectural decisions.
• Ensure the security and compliance of healthcare data, adhering to HIPAA regulations.
• All employees are responsible for adherence to the Capital Rx Code of Conduct, including reporting noncompliance.

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
• Minimum 6 years (4 years with a Master’s degree) of experience in industry focusing on ML solutions development and production deployment.
• At least 2 years of experience in Engineering Management with teams of 4 or more engineers.
• Strong grasp of OOP, design patterns, efficient algorithms, and quality software development.
• Strong proficiency in Python and familiarity with ML libraries such as PyTorch.
• Familiarity with cloud platforms such as AWS or Azure.
• Familiarity with GenAI services such as OpenAI GPT, Anthropic Claude, Google Gemini, etc.; experience developing and fine-tuning prompts on any of the GenAI services.
• Passion for customer, innovation, product quality, service excellence, and test engineering.
• Ability to work collaboratively across multiple disciplines in a fast-paced, startup environment.
• Good written and communication skills that enable collaboration in a remote environment.

Salary Range: $200,000 - $230,000 USD

Judi Health values a diverse workplace and celebrates the diversity that each employee brings to the table. We are proud to provide equal employment opportunities to all employees and applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, medical condition, genetic information, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.