At Thorne, the business and technical problem is to lead next-generation personalization and data-driven wellness initiatives by transforming early research models into production-grade AI and machine learning systems that deliver measurable value.
Requirements
- Advanced Python skills, including FastAPI, async microservices, and ML infrastructure development.
- Hands-on experience with AWS AI/ML services (Bedrock, ECS, Lambda, OpenSearch, CloudWatch).
- Deep understanding of vector databases, retrieval architectures, and embedding pipelines.
- Strong MLOps experience (CI/CD, model registry, reproducibility, automated deployment).
- 7+ years of software or ML engineering experience, with 2+ years in production AI/ML deployment.
- Experience with TensorFlow, PyTorch, Scikit-learn, or XGBoost.
- Experience with OpenSearch, Bedrock, and other vector databases.
Responsibilities
- Collaborates with Science, Data, and Product teams to prototype and validate AI/ML models using Python, FastAPI, and modern orchestration frameworks.
- Leads efforts to productionize machine learning prototypes, ensuring scalability, reproducibility, and performance.
- Designs and deploys ML pipelines and inference services using TensorFlow, PyTorch, Scikit-learn, or XGBoost.
- Develops and optimizes agentic LLM pipelines, RAG workflows, and semantic search using OpenSearch, Bedrock, and other vector databases.
- Partners closely with IT and DevOps to operationalize innovation in a secure and compliant manner.
- Integrates LLM and generative AI APIs (OpenAI, Bedrock, Anthropic, etc.) into production systems.
- Mentors junior engineers and data scientists on best practices in experimentation, deployment, and observability.
Other
- This is a remote position.
- Background in health tech, wellness, or regulated environments (DSHEA, HIPAA) is a plus
- Develops and delivers on assigned objectives within requested timeframes.
- Works cooperatively with executives and senior managers in other departments.
- Possesses good interpersonal skills engages others in a positive manner.
