Senior Machine Learning Engineering Manager
Lead a team building AI/ML systems for healthcare benefits, including LLMs, RAG, and multimodal models, to improve claims processing and customer experience.
- Compensation
- $158K–$237K / yr
- Location
- Charlotte, North Carolina, United States; Denver, Colorado, United States; New York, New York, United States
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- Bachelor's or Master's degree in Computer Science, Machine Learning, or a related quantitative field.
- Minimum 8+ years (4 years with Masters degree) of experience in industry with a strong focus on ML solutions development and production deployment.
- At least 3+ years of experience in Engineering Management with teams of 4 or more engineers
- Experience working across the AI development lifecycle (AI DLC)
- 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 Gemma etc. Experience developing and fine-tuning prompts on any of the GenAI services
- Passion for customer, innovation, product quality, service excellence, and test engineering
- The ability to work collaboratively across multiple disciplines in an extremely fast-paced, startup environment.
- Strong written and communication skills
Full description
About Judi Health
Judi Health is a health technology company providing benefit administration solutions to employers, unions, health plans, and government entities. Judi Health replaces fragmented, outdated systems with the industry's first Unified Claims Processing™ architecture, seamlessly consolidating pharmacy and medical benefit administration on a single, secure platform. By delivering true price transparency, eliminating unnecessary middleman fees, and leveraging advanced AI-powered care delivery, Judi Health helps clients achieve unprecedented operational efficiency and service levels.
At Judi Health, we're deploying the infrastructure our country needs to deliver the healthcare we all deserve. We are the intelligence platform powering benefits plans for millions of Americans and proudly leading the next generation of care. To learn more, visit .
Location: Hybrid 3 days in office (New York, NY, Denver, CO or Charlotte, NC area)
Position Summary:
Join our mission to infuse cutting-edge AI/ML/GenAI into health benefit management as a Senior Machine Learning Engineering Manager. We are looking for an experienced software engineer with hands-on machine learning and leadership expertise to join us in expanding our AI capabilities, enabling increased productivity and magical experiences in our products and services.
In this role you will be expected to lead the design and implementation of complex AI systems that leverage ML models for NLP, NLG, multimodal data analysis, chatbots, and RAG-based QnA. We want people who like leading and working in a collaborative team environment and enjoy creating practical, efficient, and high-performance software that leverages Large Language Models (LLM), Multimodal Language Models(MLM), and other ML models and techniques to build amazing capabilities for our customers, partners, and employees. Most importantly, we are a mission-oriented, high-growth startup and we are looking for folks that are excited to be part of our journey to make lasting impact towards transforming healthcare.
Responsibilities:
- 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 your team members.
- Manage a team and also contribute towards productionizing machine learning (ML) solutions in the fields of 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, including problem definition, data exploration, feature engineering, model training, validation, and deployment.
- Participate in code reviews, testing, and quality assurance processes.