Perception Engineer

About the role

Mach Industries is a defense technology company focused on developing next-generation autonomous defense platforms. The company was founded in 2022 and operates with startup agility and ambition, aiming to redefine the future of warfare through cutting-edge manufacturing and innovation.

Key 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.

Requirements

• Production C++ on Linux and Python for ML/tooling; profiling, optimization, and rigorous testing discipline;
• Experience diving into 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.

Preferred qualifications

• Multi-modal perception experience (EO/IR + radar/LiDAR/RF) at the decision or feature level;
• Robustness and safety: adversarial/rare-event testing, long-horizon reliability metrics, dataset shift/drift monitoring;
• Physics-aware imaging: radiometric correction, NUC/FFC, atmospheric effects modeling; synthetic data/simulation for coverage;
• MLOps and data infra: SQL/Parquet, dataset/versioning tools, CI-based validation; scalable training on multi-GPU.