Palantir
Software Engineer - Hosted Model Infrastructure
Palo Alto, CA · On-site · Unspecified
- Discipline
- Software
- Industry
- Government
Spec sheet
Automatically summarized from the employer’s posting. Check the original description below for full requirements.
Software Engineer position at Palantir in Palo Alto, CA focuses on enabling ML models in production across environments. The role requires owning end-to-end services from inference to deployment pipelines and observability.
Required
- software engineering
- ML model deployment
- inference engines
- GPU scheduling
- deployment pipelines
- observability
- Palantir platform integration
Preferred
- edge deployment
- air-gapped / defense environments
- GPU resources
Employer description
A World-Changing Company
Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more.
The Role
We are a software engineering team with expertise in enabling ML models in production. We deploy AI models to run in variety of environments: air-gapped government networks, forward-deployed defense environments, edge nodes, and enterprises with strict data sovereignty requirements. Our customers rely on us for frontier AI capabilities running on hardware they control, often with constrained GPU resources and limited direct access. Rising to that challenge and meeting those expectations is what Palantir’s excels at.
We treat models like any other software: continuously tested, continually delivered, packaged for reproducible deployment, and built for long-term maintainability. You will own services end-to-end, and work across the full stack, from inference engines, GPU scheduling to deployment pipelines, observability, and integration with Palantir’s platform. The goal is to deliver new models and capabilities quickly and continuously.
Join us if you want to solve problems at the intersection of infrastructure and machine learning that directly enable critical customers.
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