Top Python Jobs in Washington, DC

Integrate and deploy autonomy software onto unmanned aircraft, prepare flight-ready systems, support on-site flight tests, debug hardware/software issues, collect and analyze flight data, collaborate across autonomy, GNC, and test teams, and support certification, compliance, and process improvements.

Own and maintain native C++ build systems for autonomous aircraft. Improve developer velocity by reducing build/test cycle time, integrate CI with HIL and simulation, implement monitoring and alerts, troubleshoot build/test failures, and collaborate with engineers to design and deploy DevEx/DevOps solutions.

Design, implement, and maintain C++ and Python software for cross-platform, distributed real-time systems. Integrate third-party software/hardware and simulation tools, develop APIs/messaging (gRPC/REST/ZeroMQ), debug threading/timing issues, and improve CI/CD pipelines with Docker, CMake, Conan, and GitLab CI while practicing test-driven development and collaboration.

Lead integration, verification, and flight testing of Hivemind autonomy on Group 5 ACP systems. Own test strategy and execute multi-phase SIL/HIL/simulation/ground/flight campaigns, manage test readiness, safety-of-flight, and risk decisions, coordinate OEMs, government customers, and cross-functional teams, and define mission-level performance metrics.

Lead design and prototyping of generative AI experiences for autonomy development; drive UX for Hivemind products; perform user research, collaborate with CTO and product leads, and deliver reference implementations and integrations across full-stack web and edge systems.

Design and implement tactical autonomy algorithms and high-performance software for unmanned air/land/sea platforms. Build behavior architectures, integrate classical and learning-based methods, run simulations and field tests, analyze mission data, and support defense programs and deployments.

Lead design and integration of high-performance C++ and Python systems across distributed, real-time environments. Own CI/CD, containerization, build tooling, messaging/APIs, and debugging. Drive end-to-end integration, mentor engineers, set technical direction, and evaluate technologies to improve system performance and stability in autonomy and simulation domains.

Lead and grow a small autonomy engineering team to design, integrate, validate, and field autonomy software for launched effects. Own delivery, hiring, mentoring, technical direction, ICDs, pre-deployment validation, live test support, hardware/software debugging, and cross-team collaboration for multi-agent and air-gapped fleet deployments.

Become an expert in the Hivemind autonomy stack, create and deliver hands-on technical training, develop training materials and documentation, support customer debugging, and collaborate with product and engineering to improve adoption and training practices. Role includes ~30% travel for in-person customer engagements.

Develop and maintain Python-based analytics, automated test orchestration, and scenario-generation pipelines for autonomy simulation. Build adapters in C++/Python, analyze logs/rosbags, deploy distributed orchestration with Terraform/Kubernetes, and create telemetry ingestion and reporting frameworks to validate AI Pilot behaviors across secure and commercial environments.

Lead and grow a team of autonomy engineers to stand up autonomy on novel platforms (space, maritime, rotorcraft), own delivery from design through fielding, write and integrate latency-sensitive autonomy code, coordinate with platform and cross-functional teams, support live tests and deployments, and evolve R&D efforts into longer-term programs.

Lead and grow a 5–10 engineer autonomy integration team for V-BAT/X-BAT, owning delivery, hiring, mentoring, and technical health. Drive integration of autonomy software (mission behaviors, VTOL transitions, multi-agent coordination), collaborate tightly with aircraft, perception, and capability teams, run ICDs and field tests, and support live exercises and deployments (20–30% travel).

Lead simulation-driven testing and automation for autonomy software: develop automated regression/integration/system tests, build and maintain simulation-based test frameworks and tools (SIL/HIL/VIL), diagnose issues with developers, scale simulation infrastructure, create test plans, and integrate test coverage into CI/CD pipelines using Python.

Integrate autonomy software onto unmanned aircraft, prepare and validate flight-ready systems, support on-site flight tests, debug hardware/software integration, capture and analyze flight data, collaborate with autonomy/GNC/systems teams, improve integration processes, and assist with certification and compliance. Travel ~30-40% for tests and field events.

Design, implement, and deploy safety-critical navigation and state estimation systems for aerospace platforms. Develop EKF and GNSS/INS integration, multi-sensor fusion for GPS-denied environments, FDIR and integrity monitoring, and V&V test plans. Support certification, requirements allocation, performance analysis, flight test evaluation, and provide technical leadership and mentoring.

Design, develop, and field high-performance Ground Control Station and C2 software using C++/Qt/QML and QGroundControl. Lead architecture and technical direction, mentor engineers, define APIs/ICDs, debug integration/latency issues, support field tests, implement post-mission debrief tools, and ensure interoperability with C2 standards.

Integrate autonomy software onto unmanned aircraft, prepare and validate flight-ready systems, support on-site flight tests, debug hardware/software interactions, capture and analyze flight data, collaborate with autonomy/GNC/systems teams, and support certification and compliance. Frequent travel (~30-40%) for field tests.

Lead simulation-driven testing and automation for autonomy software. Build and maintain simulation-based test frameworks and test harnesses (SIL/HIL/VIL), develop Python tooling for test automation and data analysis, execute regression/integration tests, diagnose issues with developers, integrate tests into CI/CD, and maintain test documentation and metrics for mission-critical autonomous aircraft systems.

Lead design and delivery of backend and data-driven services: translate product requirements into technical designs, implement and deploy production cloud services, mentor engineers, review code, drive technical decisions, and own the technical excellence and roadmap for your team.

Contribute production-quality code to Palantir products (Gotham, Foundry, Apollo) across the full product lifecycle. Collaborate with engineers, PMs, designers, and users; prototype, implement, and ship features. Learn on the job with mentorship and opportunities to engage directly with customers to understand real-world use cases.

Join Palantir Production Infrastructure to build and operate large-scale platforms (Rubix, Apollo) and core deployment, observability, and Kubernetes-based PaaS tooling. Own full product lifecycle, collaborate with cross-functional teams, and deploy software supporting civil and defense customers while learning from a paired mentor.

Develop and ship production-quality software for Palantir's Gotham defense product. Work across the product lifecycle on features like geospatial tools and release infrastructure, collaborate with cross-functional teams, and be mentored while contributing code and prototypes to mission-critical systems.

Interns contribute production infrastructure code across deployment, observability, and environment platforms (Kubernetes PaaS, Apollo, Rubix). Paired with a mentor, they design, implement, and ship features, collaborate with cross-functional teams, and may observe field deployments with government or defense partners.

Build and ship scalable software for Palantir Gotham across the full product lifecycle. Collaborate with cross-functional teams, work directly with users to understand problems, and contribute high-quality code while paired with a mentor. May involve field visits to customers to learn mission needs.

The Software Engineer will build and operate ML model infrastructure, integrating AI models in various environments, ensuring security, reliability, and performance throughout the deployment process.