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# Senior Autonomy Software Engineer

- **Company:** Phyton Talent Advisors LLC
- **Location:** Los Angeles, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Computer Vision, C++ (Programming Language), Middleware, Embedded Software, Global Positioning Systems (GPS), Python (Programming Language), Machine Learning, Motion Planning, OpenCV, Open Source Technology, Sensor Fusion, Scripting, AI Coding Agents, Production Code, Machine Learning Operations
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25303_832d481873682660c060c325a583a097

## About the Role

* Deep, practical experience in perception, navigation or planning for real-world autonomous systems
 * A track record of building autonomy from scratch, not extending a mature stack
 * Production code in a systems language, not just prototypes, notebooks or papers
 * Comfort writing your own architecture and glue instead of relying on a framework
 * Smart, skeptical use of AI coding tools to move fast without shipping slop
 * First-principles thinking and a bias for speed, * Relevant experience with hands-on autonomy, perception, robotics or production software
 * Deep proficiency in C, C++ or Rust, plus a scripting language such as Python
 * Willingness to support field testing and trials, * UAVs, drones, surface or underwater vehicles, ground robotics, aerospace or other real-world autonomous platforms
 * Defense programs
 * GPS-denied, communications-constrained or low-visibility operating environments
 * Deploying ML models on edge compute
 * Building sim, replay, Monte Carlo, SIL or HIL test environments
 * Safety-critical or high-reliability software
 * Early-stage startup experience, or a greenfield program inside a larger organization

## Description

This is the first dedicated autonomy hire, and a Responsible Engineer role modeled on the SpaceX approach: you own the autonomy and perception stack, you make the architectural calls, and the buck stops with you (with real peer review along the way). It's hands-on IC work. The head of autonomy is handing off his own IC work and wants you to tell him how the system should be built.

The expectation is clear: stand up the vehicle's autonomy architecture from a blank sheet and get a working product running in about 90 days. You won't write every component from zero. Proven open-source tools (YOLO, OpenCV and the like) come in where they make sense. But there's no ROS; the glue, the middleware and the overall architecture are yours to write.

The stack spans three areas, and the first hire needs to be strong across all of them:

 * Perception. Detect, recognize, classify and track what the vehicle's sensors see, using machine learning and classical computer vision, on constrained edge compute.
 * Navigation and localization. Know where the vehicle is without GPS: state estimation, sensor fusion and mapping.
 * Planning and decision-making. Mission planning, path planning, obstacle avoidance, and recovering safely when something goes wrong., What You'll Own
 * Requirements, architecture and the hard tradeoffs, often with incomplete information
 * Production autonomy software in C, C++ or Rust, running within real compute, memory, latency and power limits
 * Model training, evaluation and deployment for perception
 * The simulation, replay, SIL and HIL environments used to test autonomy before it goes in the water
 * Sensor selection and sensing architecture, alongside avionics and embedded software
 * Field testing and sea trials, and root-cause analysis from logs and telemetry afterward
 * Mentoring the autonomy engineers who join after you, Engineers who have built an autonomy system from a blank page and shipped it to a real vehicle, ideally more than once. You can name the filter, the planner, the model and why you chose it. You've owned the decision, not just implemented it., * In about 90 days, the vehicle runs on an autonomy architecture you designed and can defend
 * Your perception, navigation and planning are running in the water during range testing, and you're the one reading the logs
 * The test and replay tooling you built lets the team ship changes with confidence
 * As the autonomy team grows, you're a natural candidate to lead it