Our hiring partner is building the technology infrastructure the nation needs to deliver the healthcare everyone deserves. As a health technology company providing benefit administration solutions to employers, unions, health plans, and government entities, they are replacing fragmented, outdated systems with an industry-first unified claims processing architecture. This platform seamlessly consolidates pharmacy and medical benefit administration onto a single, secure system - delivering true price transparency, eliminating unnecessary middleman fees, and leveraging advanced AI-powered care delivery.

The company is the intelligence platform powering benefits plans for millions of Americans and is proudly leading the next generation of care. They are now expanding their AI capabilities to enable increased productivity and magical experiences across their products and services, and they are seeking an experienced ML engineer to help design and implement complex AI systems at the forefront of healthcare innovation.

Why This is a High-Impact Opportunity

1. Build Frontier AI Systems: Design and implement complex AI systems leveraging ML models for NLP, NLG, multimodal data analysis, chatbots, and RAG-based Q&A in a mission-critical domain.
2. Shape Agentic Architectures: Design multi-agent orchestration patterns and evaluate architectural tradeoffs for scaling agent development across teams.
3. Own the Full ML Lifecycle: Work across problem definition, data exploration, feature engineering, model training, validation, and deployment, productionizing solutions that directly impact healthcare outcomes.
4. Mission-Driven Work: Join a high-growth, collaborative startup environment where your contributions directly shape the future of AI-driven healthcare automation.

About the Role

We are seeking a Senior Machine Learning Engineer with a passion for applying AI/ML concepts to difficult problems and developing scalable solutions. In this role, you will design and implement complex AI systems that leverage ML models for NLP, NLG, multimodal data analysis, chatbots, and RAG-based Q&A.

The ideal candidate enjoys working in a collaborative team environment and creating practical, efficient, and high-performance software that leverages LLMs, multimodal language models, and other ML techniques to build amazing capabilities for customers, partners, and employees.

Key Responsibilities

1. Design, develop, and productionize ML solutions in the fields of document understanding, search and Q&A, GenAI, and virtual agents.
2. Develop and maintain backend services using Python, focusing on AI-driven applications.
3. Design and implement APIs for seamless integration with AI models and services.
4. Design multi-agent orchestration patterns (e.g., supervisor/subagent architectures, tool-use boundaries, human-in-the-loop gating) and evaluate architectural tradeoffs for scaling agent development across teams.
5. Contribute to the development and scaling of retrieval/search infrastructure underlying RAG systems (e.g., vector search clusters, embedding pipelines, capacity planning).
6. Build and maintain CI/CD pipelines supporting the build, test, and deployment of agentic AI systems.
7. Collaborate with product managers, engineers, and other stakeholders as a specialist and subject matter expert in machine learning.
8. Work across the complete lifecycle of ML model development, including problem definition, data exploration, feature engineering, model training, validation, and deployment.
9. Participate in code reviews, testing, and quality assurance processes.
10. Troubleshoot and resolve technical issues related to AI model integration, deployment, and backend services.
11. Implement system telemetry, A/B testing, and other statistical methods to validate the effectiveness of AI models. Ensure the integrity and robustness of ML solutions by developing automated testing and validation processes.
12. Document and communicate development processes, system designs, and architectural decisions.
13. Ensure the security and compliance of healthcare data, adhering to HIPAA regulations.

Required Qualifications

1. Bachelor's or Master's degree in Computer Science, Machine Learning, or a related quantitative field.
2. Minimum 6+ years of experience in industry with a strong focus on ML solutions development and production deployment.
3. Strong grasp of object-oriented programming, design patterns, efficient algorithms, and quality software development.
4. Strong proficiency in Python and familiarity with ML libraries such as PyTorch.
5. Statistical Machine Learning and Artificial Intelligence in the context of NLP, Speech, RAG, Virtual Agents, and/or Document Processing technologies.
6. Familiarity with cloud platforms such as AWS or Azure, including hands-on experience with containerized deployments.
7. Familiarity with GenAI services such as OpenAI GPT, Anthropic Claude, Google Gemma, etc., including experience developing and fine-tuning prompts.
8. Experience designing evaluation frameworks for non-deterministic/agentic AI systems.
9. Excellent problem-solving skills, attention to detail, and a strong capacity for logical thinking.
10. Passion for customer, innovation, product quality, service excellence, and test engineering.
11. The ability to work collaboratively across multiple disciplines in an extremely fast-paced, startup environment.
12. Experience working with microservices/an API-based application paradigm.
13. Good written communication skills that enable collaboration in a remote environment.

Apply Now

If you are a senior ML engineer with deep expertise in building and productionizing AI systems, and you are excited by the challenge of applying frontier AI to mission-driven healthcare, we encourage you to apply. This is a defining opportunity to shape the future of AI-driven healthcare automation at scale.