Lead AI/ML Engineer - Lead Optimization

Boston, MA, US

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Description

About Connie Health

Connie Health is a fast-growing Medicare brokerage on a mission to empower older Americans to make confident, worry-free Medicare plan decisions. We offer a tech-enabled Medicare navigation platform that combines an AI-driven technology with local Medicare experts to help people select optimal healthcare plans and navigate their benefits. Our culture is mission-driven, collaborative, and innovative, as we strive to transform healthcare through data-driven insights and personalized guidance. We value Relationships First, Data-Driven Decision Making, and being Accountable in delivering unbiased, high-quality advice to our customers.


Role Overview

Connie Health is seeking a versatile and experienced AI / Machine Learning Engineer to play a pivotal role in building and scaling the intelligence behind our Medicare sales platform, working at the intersection of applied machine learning, product, and infrastructure. You'll be instrumental in developing, deploying, and maintaining machine learning models and systems, working across the spectrum from cutting-edge Large Language Model (LLM) technologies to more traditional ML approaches (classical models and neural nets), empowering our customers to make informed healthcare decisions and our Medicare agents to provide exceptional service. This is a player-coach role leading the Lead Optimization team, owning our top-of-funnel AI/ML systems. This role requires a blend of strong machine learning expertise, software engineering skills, and a passion for leveraging data to solve complex problems in the healthcare space. 


This is a hybrid role, based out of our new Boston office near South Station.


What You’ll Do

  • Lead a small team of AI/ML and software engineers, providing mentorship and coaching.
  • Design, build, and productionize machine learning models, from initial experimentation to full production deployment.
  • Build and maintain efficient data pipelines to support the entire ML lifecycle, ensuring high-quality data for model training, evaluation, and serving.
  • Work with cutting-edge Large Language Models (LLMs) for natural language understanding tasks, and build the Retrieval Augmented Generation (RAG) systems that enhance them.
  • Evaluate and select appropriate AI/ML technologies, frameworks, and tools to meet project requirements and continuously enhance our tech stack.
  • Implement best practices for MLOps, covering everything from version control and continuous integration/continuous deployment (CI/CD) for ML models to robust monitoring and alerting systems.
  • Stay current with the latest advancements in AI/ML and apply innovative techniques to improve our products and services.

Requirements

Minimum Qualifications

  • Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
  • 5+ years of professional experience focused on applied machine learning or AI.
  • 3+ years of experience with Python and experience with popular ML frameworks, such as scikit-learn, PyTorch, TensorFlow, Spark MLlib, or XGBoost. 
  • Experience as a tech lead and/or managing a small team of engineers.
  • Experience designing and building scalable data and annotation pipelines, as well as evaluation systems for AI model quality.
  • Experience working with modern LLMs, such as GPT, Claude, Llama, Gemini, or DeepSeek.
  • Strong understanding of machine learning fundamentals
  • Experience with SQL and working with relational databases.
  • Excellent problem-solving skills and the ability to work independently and collaboratively in a fast-paced environment.
  • Strong communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.

Preferred Qualifications

  • Master’s or Ph.D. in a related field.
  • Experience with Natural Language Processing (NLP) techniques and libraries.
  • Experience building Retrieval Augmented Generation (RAG) systems, vector databases, and embeddings.
  • Experience with AI infrastructure and MLOps, including observability, CI/CD, and automation for ML workflows.
  • Prior experience in the healthcare or insurance industry, particularly with Medicare.
  • A product mindset with the ability to tie technical work to user outcomes and business impact.

Why Join Connie Health?

  • Great Culture.
  • Comprehensive health insurance plans.
  • Competitive salary and equity packages.
  • Unlimited vacation policy and generous holiday observances.
  • Monthly work from home stipend.
  • The opportunity to be part of a values-driven and hardworking group of people.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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Tags: CI/CD Claude Computer Science Data pipelines Engineering Gemini GPT LLaMA LLMs Machine Learning ML infrastructure ML models MLOps Model training NLP Pipelines Python PyTorch RAG RDBMS Scikit-learn Spark SQL TensorFlow XGBoost

Perks/benefits: Career development Competitive pay Equity / stock options Gear Health care Home office stipend Insurance Unlimited paid time off

Region: North America
Country: United States

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