Machine Learning Engineer (LLMOps)
Own LLM training/fine‑tuning, retrieval pipelines, evaluation, and productionization.
Job Details
Machine Learning Engineer (LLMOps)
Remote • Full‑time
Own LLM training/fine‑tuning, retrieval pipelines, evaluation, and productionization.
You will collaborate with product engineers to deliver robust AI systems with clear SLAs.
Responsibilities
- 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
Requirements
- 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)
Nice to Have
- 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
Hiring Process
- Intro call
- ML systems interview
- Practical exercise
- Offer
Compensation
Competitive salary + bonus; relocation support if desired