Senior ML Infrastructure 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.
• A 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: $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.