Senior MLOps Engineer

Responsibilities

• Construct optimized data pipelines to run ML models.
• Evolve our data engine architecture to scale high-fidelity labels, reduce annotation costs, and accelerate ML iteration cycles.
• Integrate foundation models (LLMs, VLMs, and multimodal models) to automate and enhance labeling, quality assurance, and data discovery.
• Leverage software-in-the-loop and hardware-in-the-loop testing.
• Interact with the DoD customer to understand their use cases, requirements, and triage needs during field events to deliver a superior customer experience.

Requirements

• 5+ years of relevant work experience.
• Familiarity with modern ML infrastructure, data-centric AI approaches and running large-scale jobs on GPUs.
• Created or worked on microservices and/or databases for data-oriented software.
• Hunger to learn and grow into a position of ownership and impact on a new product team.
• U.S. citizenship (legally required) and eligibility to obtain a security clearance.

Nice-to-Haves

• Full-stack experience with React, TypeScript, Python, Golang or similar.
• Experience with Docker, Kubernetes, Opensearch and Postgres.
• Direct experience with foundation models, including LLMs and VLMs, for data automation tasks.
• Background in autonomous driving or robotics perception.
• Experience with active learning, auto-labeling, or human-in-the-loop ML systems.

Compensation

Base salary range for this full-time position: $150,000 - $240,000 USD annually. Total compensation package may also include equity, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off.