About the Role
About Mach Industries
Founded in 2022, Mach Industries is a rapidly growing defense technology company focused on developing next-generation autonomous defense platforms. At the core of our mission is the commitment to delivering scalable, decentralized defense systems that enhance the strategic capabilities of the United States and its allies. With a workforce of approximately 350 employees, we operate with startup agility and ambition.
Our vision is to redefine the future of warfare through cutting-edge manufacturing, innovation at speed, and unwavering focus on national security. We are dedicated to solving the next generation of warfare with lethal systems that deter kinetic conflict and protect global security.
The Role
Mach Industries is building an AI‑forward autonomy stack for contested environments where GPS and other sensing is unavailable or unreliable. As a member of our team, you will design and implement state-of-the-art estimation and sensor-fusion algorithms that power robust navigation across all of our product lines. You will work at the intersection of perception, state estimation, and embedded systems to bring research-grade algorithms to rugged, real-world deployments.
Key Responsibilities
- Prototype and productionize vision navigation and targeting features end-to-end from sim to HITL to flight with production C++.
- Turn detections (EO/IR/RF/radar) into well-posed measurement models with latencies/covariances; make the estimator decision‑aware without corrupting state.
- Stabilize GNSS to VIO handover (adaptive covariances, gating, hysteresis, reset‑less alignment) to eliminate jumps and estimator resets.
- Build and optimize real-time software on Linux/embedded; profile CPU/GPU, vectorize hot paths; optional CUDA/TensorRT on Jetson hardware.
- Own calibration and time-sync across IMU/cameras/radar/LiDAR/GNSS; validate in flight.
- Create evaluation pipelines and dashboards for drift, handover stability, relocalization, track quality.
- Implement fault detection and graceful degradation for harsh conditions (blur, low‑light, vibration, RF denial).
- Integrate global aids (maps, magnetics, radar) for long‑term consistency and loop‑closure robustness.
Required Qualifications
- Stellar software ability: Modern C++ on Linux; Python for tooling/analysis; strong debugging, profiling, testing discipline.
- SLAM/state estimation: Error-state EKF/UKF, factor graphs, nonlinear least-squares (Ceres/GTSAM), observability and covariance tuning.
- Vision experience VIO/SLAM, camera models, optical flow/feature tracking; comfort with deep learning for detection/seg/pose (PyTorch) and on-edge deployment.
- Sensor integration: IMU strapdown and biases, GNSS/RTK; multi-camera, LiDAR, radar, magnetometer, barometer.
- Ship and fly: Proven research-to-production delivery and field testing on real platforms.
- 5 years of experience with either a BS/MS/PhD in Computer Science, Robotics, Electrical/Aerospace Engineering, or related field, or equivalent practical experience.
Preferred Qualifications
- Experience with CUDA/TensorRT/ONNX Runtime; NVIDIA Jetson pipelines.
- Exposure to ROS 2, PX4/ArduPilot integration.
- Strong data practices: data validation in CI, SQL/Parquet, reproducible datasets.
- Experience in contested/denied RF, low-light/night, high-vibration environments.
- Rust for systems tooling; Docker for reproducibility.
Disclosures
This position may require access to information protected under U.S. export control laws and regulations, including the Export Administration Regulations (EAR) and the International Traffic in Arms Regulations (ITAR). Please note that any offer for employment may be conditioned on authorization to receive software or technology controlled under these U.S. export control laws and regulations without sponsorship for an export license.
Mach participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.
Requirements
Modern C++
Proficiency in modern C++ programming on Linux is essential.
SLAM/State Estimation
Experience with SLAM and state estimation techniques is required.
Vision Experience
Familiarity with VIO/SLAM and deep learning for detection and segmentation is necessary.
Sensor Integration
Knowledge of integrating various sensors like IMU, GNSS, and LiDAR is important.
Research to Production
Proven ability to deliver research projects to production and field testing is required.
5 Years Experience
A minimum of 5 years of relevant experience or equivalent education is necessary.
Nice to Have
Experience with CUDA and TensorRT for optimization is a plus.
Familiarity with ROS 2 and PX4/ArduPilot is preferred.
Strong data validation practices in CI and reproducible datasets are beneficial.
Experience with Rust for systems tooling is a nice addition.
Benefits
Health Insurance
Comprehensive health insurance plans are provided.
Remote Work
Flexible remote work options are available.
Learning Budget
A budget for continuous learning and development is offered.