Palantir

Dev

SoftwareEngineer-HostedModelInfrastructure

$175–250k ~AI est. Washington, District of Columbia, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Software Engineer - Hosted Model Infrastructure at Palantir. Skills: MLOps, Infrastructure, Software Engineering, DevOps. Build high-performance model serving infrastructure. Integrate with security models”

What You'll Achieve.

Deliver new models quickly; Deliver new capabilities continuously

Industry & Context.

Dev
Problems you'll solve

Debugging; Performance troubleshooting

Eligibility Requirements

US Security clearance

What They're Looking For.

Must Have

4+ years professional software engineering experience, Engineering background in CS, Math, Software Eng, Physics, or similar, Proficiency in programming languages (Java, C++, Python, Rust, or similar), Experience with containers, Experience with Kubernetes, Experience deploying backend services in production, Written and verbal communication skills, Ability to iterate quickly with teammates, Ability to hold a high bar for quality

Nice to Have

Familiarity with Python ML ecosystem, Active US Security clearance, Eligibility and willingness to obtain US Security clearance

What You'll Do.

Build high-performance model serving infrastructure

Integrate with security models

Integrate with hardware constraints

Integrate with inference engines

Design intelligent request handling

Handle authentication

Handle concurrency control

Build packaging pipelines

Maintain packaging pipelines

Enable fast model rollouts

Enable secure model rollouts

Enable reliable model rollouts

Develop observability for AI systems

Enable easy service monitoring

Enable fast incident triage

Enable fast incident resolution

Debug performance problems

Design testing infrastructure

Run testing infrastructure

Design benchmarking infrastructure

Run benchmarking infrastructure

Validate model deployments

Work with product teams

Understand requirements

Debug production issues

Integrate hosted model infrastructure

Integrate with Palantir's deployment systems

Integrate with Palantir's configuration systems

Integrate with Palantir's identity systems

How You'll Work.

Team & Collaboration

Work across multiple languages; Work across layers of the stack; Iterate quickly with teammates; Work with product teams; Work with customers

Communication Scope

Written communication; Verbal communication

Full Job Description

## 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. ## Technologies We Use Different backend languages, including Java, Rust, Python and Go Model serving engines for GPU-accelerated inference Docker and Kubernetes for containerization and orchestration Industry-standard build tooling, including Gradle and GitHub ## Core Responsibilities Building high-performance model serving infrastructure that integrates with security models, hardware constraints, and different inference engines Designing intelligent request handling including authentication, rate limiting, concurrency control, and audit logging for multi-tenant model access Bui

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