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 ML Engineer to design, develop, and deploy AI capabilities, integrating predictive analytics and NLP to solve complex problems 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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