Software Engineer, Localization

Mach Industries • Huntington Beach, CA

82d

About The Position

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.

Requirements

• Production C++ on Linux and Python for ML/tooling; profiling, optimization, and rigorous testing discipline.
• 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.
• BS/MS/PhD in CS/EE/Robotics or similar, or equivalent experience; track record shipping ML models to production.

Nice To Haves

• 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.

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.

Benefits

• Health insurance
• Retirement plans
• Opportunities for professional development

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Master's degree
• Number of Employees: 101-250 employees