Real-Time Autonomy Perception Engineer

Mach-Industries; Los Angeles (CA); On-site; USD 125,000 - 220,000; Full time

Benefits offered by this job

Health insurance

Equity participation

Professional development

Retirement plans

Paid time off

Job summary

Mach Industries in Los Angeles is seeking a Perception Engineer to design, train, and deploy vision and multi-sensor perception systems for autonomous defense platforms. You’ll work across deep learning, computer vision, and embedded systems to bring research-grade algorithms to production deployments.

You will build detection/segmentation networks for EO/IR imagery, optimize for real-time embedded inference on Jetson-class hardware, and integrate radar/LiDAR/RF cues with fusion.

Qualifications

• Production C++ on Linux and Python for ML/tooling.
• CUDA backends for performance optimization and debugging.
• Strong with modern detection/segmentation/tracking (e.g., Retina/FCOS/DETR/Mask2D/Video models) and training/fine-tuning in PyTorch.
• Proven experience building large, diverse datasets; labeling/QA pipelines; augmentation; experiment tracking; and reproducible training.
• Hands-on with model compression (INT8/FP16), runtime optimization, and real-time constraints.
• EO/IR imagery experience and working with real flight/test data in challenging environments.
• 7+ years of experience with either a BS/MS/PhD in CS/EE/Robotics or similar, or equivalent experience; track record shipping ML models to production.

Responsibilities

• Build and refine detection/segmentation/tracking architectures (CNN/Transformer) for EO/IR and multi-spectral imagery; drive foundation-scale datasets, training recipes, and robust generalization to long-tail and degraded conditions.
• Stand up training/eval pipelines (PR/ROC, mAP, latency, robustness suites); implement continuous regression testing and model-update loops from field data.
• Optimize models for real-time embedded inference (quantization/pruning, TensorRT/ONNX Runtime), profile CPU/GPU, and meet tight throughput/latency targets on Jetson-class hardware.
• Combine vision outputs with auxiliary sensing (e.g., radar/LiDAR/RF cues) for confirm/deny, association, and track management using decision-level fusion.
• Create visualization, triage, and root-cause tools for rapid insight from simulation, HITL, and flight logs; define end-to-end test plans with hardware and flight teams.
• Instrument health metrics, drift detection, and graceful degradation; write clear tests and documentation mapped to performance requirements.
• Perform simulation-based testing with high-fidelity sensor models and validate algorithms using real-world datasets.

Skills

C++

Linux

Python

CUDA

Profiling

Optimization

Testing

PyTorch

CNN/Transformer

Deep learning

Education

BS/MS/PhD in CS/EE/Robotics

Tools

TensorRT

ONNX Runtime

Job description

Mach Industries in Los Angeles is seeking a Perception Engineer to design, train, and deploy vision and multi-sensor perception systems for autonomous defense platforms. You’ll work across deep learning, computer vision, and embedded systems to bring research-grade algorithms to production deployments.

You will build detection/segmentation networks for EO/IR imagery, optimize for real-time embedded inference on Jetson-class hardware, and integrate radar/LiDAR/RF cues with fusion.