Role overview

Senior ML Engineer (ML/AI)

Requirements and responsibilities

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Lyra is for you if you:

  • Thrive on working with brilliant teammates to solve complex, meaningful problems
  • Are passionate about making a social impact and supporting people at their most challenging moments
  • Enjoy cross-functional collaboration with physicians, therapists, data scientists, data analysts and product managers

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.

Qualifications

  • 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

Preferred Qualifications

  • 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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Browse stack
FocusEngineeringRole area
Seniority signalSeniorCandidate level
StackAWS, Docker, JavaPrimary skills
Location39 accepted countriesEligibility

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