ML Ops Engineer — Agentic AI Lab (Founding Team)

About the Role

ML Ops Engineer — Agentic AI Lab (Founding Team) — Location : San Francisco Bay Area — Type : Full-Time — Compensation : Competitive salary + meaningful equity (founding tier)

Backed by 8VC, we're building a world-class team to tackle one of the industry’s most critical infrastructure problems.

Our AI Lab is pioneering the future of intelligent infrastructure through open-source LLMs, agent-native pipelines, retrieval-augmented generation (RAG), and knowledge-graph-grounded models.

We’re hiring an ML Ops Engineer to be the glue between ML research and production systems — responsible for automating the model training, deployment, versioning, and observability pipelines that power our agents and AI data fabric.

You’ll work across compute orchestration, GPU infrastructure, fine-tuned model lifecycle management, model governance, and security.

Responsibilities

• Build and maintain secure, scalable, and automated pipelines for :
• LLM fine-tuning, SFT, LoRA, RLHF, DPO training
• RAG embedding pipelines with dynamic updates
• Model conversion, quantization, and inference rollout
• Manage hybrid compute infrastructure (cloud, on-prem, GPU clusters) for training and inference workloads using Kubernetes, Ray, and Terraform
• Containerize models and agents using Docker, with reproducible builds and CI / CD via GitHub Actions or ArgoCD
• Implement and enforce model governance : versioning, metadata, lineage, reproducibility, and evaluation capture
• Create and manage evaluation and benchmarking frameworks (e.g. OpenLLM-Evals, RAGAS, LangSmith)
• Integrate with security and access control layers (OPA, ABAC, Keycloak) to enforce model policies per tenant
• Instrument observability for model latency, token usage, performance metrics, error tracing, and drift detection
• Support deployment of agentic apps with LangGraph, LangChain, and custom inference backends (e.g. vLLM, TGI, Triton)

Desired Experience

Model Infrastructure :

Automation + Infra

Agent + Data Pipeline Support

Security & Governance

Preferred Stack

Mindset & Culture Fit

What We’re Looking For

Experience :

Mindset :

Why This Role Matters

Your work will enable models and agents to be trained, evaluated, deployed, and governed at scale — across many tenants, models, and tasks. This is the backbone of a secure, reliable, and scalable AI-native enterprise system. If you dream about using AI to solve some really hard real world problems – we would love to hear from you.

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