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Machine Learning Engineer (LLMOps)

Own LLM training/fine‑tuning, retrieval pipelines, evaluation, and productionization.

You will collaborate with product engineers to deliver robust AI systems with clear SLAs.

What you will work on

  • Build data pipelines, labeling workflows and evaluation suites
  • Fine‑tune models (SFT/LoRA), manage embeddings and retrieval
  • Productionize inference (vLLM/TensorRT‑LLM) and monitor drift
  • Implement safety/guardrails and cost/perf optimizations
  • Document playbooks and incident response procedures

What you bring

  • 3+ years in ML/Applied AI with production systems
  • Strong Python; experience with PyTorch/JAX and vector stores
  • MLOps/LLMOps tooling (Weights & Biases, Ray, Kubeflow, Airflow)

Useful experience

  • Experience with RAG benchmarks and human evaluation
  • Kubernetes, GPUs and observability (Prometheus/Grafana)
  • Security/privacy for AI systems (PII handling)

What we offer

  • Remote work and flexible PTO
  • Compute/GPU budget
  • Conference travel support

Interview process

  • Intro call
  • ML systems interview
  • Practical exercise
  • Offer

Compensation

Competitive salary + bonus; relocation support if desired