Summary
Written in English from the original postingLyra Health is hiring a Senior AI/ML Platform Engineer to build machine learning and generative AI platforms used across the company. The role involves creating backend infrastructure and services for scalable, resilient, and performant AI products, as well as deploying and maintaining applications in production. It requires strong Python experience and familiarity with modern web frameworks, containerization, Kubernetes, databases, vector databases, LLM orchestration, and observability tools.
Job description
We are looking for an experienced Senior AI/ML Platform Engineer who is eager to build the platforms, infrastructure and services necessary to deliver ML and generative AI based products that make a significant impact within the organization. The ideal candidate will be enthusiastic about taking ownership of their work, spearheading cross-functional projects, and providing guidance and mentorship to other team members.
Responsibilities
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Thrive on working with brilliant teammates to solve complex, meaningful problems
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Are passionate about making a social impact and supporting people at their most challenging moments
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Enjoy cross-functional collaboration with therapists, data scientists, engineers and product managers
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Be part of a team working on building our machine learning and generative AI platforms that will be used by teams across the company
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Create the necessary backend infrastructure and platform to enable scalable, resilient and highly performant solutions
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Build services that are used in machine learning and AI based products
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Deploy and manage various applications in production
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And of course, you will be coding every day!
Lyra is for you if you:
In this role, you will:
Qualifications
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6+ years of experience delivering production ready products
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Ability to write high-quality code in Python
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Experience with modern async Python web frameworks (e.g., FastAPI) and handling data streaming (WebSockets, Server-Sent Events)
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Experience working with Docker and deploying applications to Kubernetes
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Experience with relational and low-latency databases
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Experience building RAG based AI solutions
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Experience setting up and maintaining vector databases
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Familiarity with LLM orchestration frameworks (e.g., LangChain, LlamaIndex) and integrating with foundation model APIs (e.g., OpenAI, Anthropic, AWS Bedrock)
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Experience with LLM observability and monitoring tools (e.g., Langfuse) to track latency, token usage, and output quality.
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A desire to learn new technologies quickly
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A love of building systems from scratch
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A thoughtful approach to balancing quality and deadlines in fast-paced settings
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Excellent communication skills with a talent for building consensus and alignment
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Strong organizational skills and the ability to distill complex
Preferred Qualifications
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Experience with Graph Databases (e.g., Neo4j, AWS Neptune) and integrating them into AI/Knowledge systems (e.g., GraphRAG)
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Experience working with Celery
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Experience defining and using Protobuf messages
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Experience writing production code in Java/Kotlin
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Experience building solutions on cloud infrastructure, particularly AWS
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Experience working with highly sensitive data in a healthcare environment
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