[Remote] Senior ML Engineer (ML/AI)
Note: The job is a remote job and is open to candidates in USA. Lyra Health is a leading provider of evidence-based mental health care, serving millions globally. They are seeking a Senior AI/ML Engineer to design, develop, and deploy AI capabilities for their platform, bridging the gap between data science and software engineering while mentoring junior engineers.
Responsibilities
- Design, train, fine-tune, and evaluate deep learning, classical ML, and foundational GenAI models (LLMs, diffusion models) to drive core product features
- Build, scale, and maintain robust ML pipelines for continuous training, evaluation, and real-time/batch inference using modern MLOps frameworks
- Collaborate with backend and frontend teams to integrate AI models into microservices, ensuring low latency, high availability, and optimal resource utilization
- Architect scalable data pipelines for preprocessing, vectorizing, and ingestion of massive structured and unstructured datasets
- Implement rigorous evaluation frameworks for model alignment, bias mitigation, guardrailing, and cost/latency optimization (e.g., quantization, distillation)
- Provide technical leadership, conduct thorough code reviews, and mentor junior/mid-level engineers on best practices in software craftsmanship and ML engineering
Skills
- 6+ years of experience deploying ML/AI solutions in production environments
- Ability to write high-quality code in Python
- Experience building RAG (retrieval-augmented generation) based solutions
- Experience setting up and maintaining vector databases
- A strong desire to work on ML/AI based products
- A desire to learn new technologies quickly
- A thoughtful approach to balancing quality and deadlines in fast-paced settings
- Excellent communication skills with a talent for building consensus and alignment
- Strong organizational skills and the ability to distill complex problems into clear priorities that move the team and business forward
- Experience defining and using Protobuf messages
- Experience working with Docker and deploying applications to Kubernetes
- Experience with relational and low-latency databases
- Experience working with Celery
- Experience building RAG (retrieval-augmented generation) based solutions
- Experience setting up and maintaining vector databases
- Experience writing production code in Java/Kotlin
- Experience building solutions on cloud infrastructure, particularly AWS
- Experience working with highly sensitive data in a healthcare environment
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