ML Engineer: Real-Time Edge AI for Autonomous Defense

Mach Industries; Huntington Beach (CA); On-site; USD 120,000 - 220,000; Full time

Benefits offered by this job

Healthcare

Dental and Vision plans

Retirement plans

Paid time off

Job summary

Mach Industries is building an AI-forward autonomy stack for contested environments where GPS sensing is unreliable. As a Machine Learning Engineer, you will own and scale the training, data, and edge-inference backbone that every vision and multi-sensor model on our product lines depends on for detection, tracking, search, navigation, and ATR.

This high-ownership role spans data infrastructure, model training, and deployment on embedded hardware in flight.

Qualifications

• Strong generalist software engineering: Python for ML and tooling, plus production C++ on Linux.
• Proven experience building ML data and training pipelines end to end: dataset construction, labeling/QA, augmentation, experiment tracking.
• Hands-on training and fine-tuning in PyTorch across modern detection/segmentation/tracking architectures.

Responsibilities

• Own and evolve the training and data infrastructure the autonomy team builds on: ingestion from flight/sim/HITL, labeling/QA workflows, dataset versioning, and reproducible dataset builds.
• Stand up and scale training/eval infrastructure: distributed multi-GPU training, experiment tracking, a model registry, and CI-based evaluation with regression gates.
• Deploy and optimize models for real-time edge inference on Jetson-class hardware (quantization/pruning, TensorRT/ONNX Runtime); profile CPU/GPU and meet latency/SWaP targets.
• Build and improve models across the portfolio as a hands-on IC: detection, segmentation, tracking, target/area search, classification/ATR, and multi-sensor fusion.
• Generate and manage synthetic data at scale (simulation + domain randomization) to cover long-tail and degraded conditions.
• Instrument runtime health, drift detection, and graceful degradation, and wire model-performance metrics back into retraining loop.
• Live close to flight data with visualization, triage, and root-cause tooling to speed up model updates.
• Partner with other autonomy disciplines across perception, localization, embedded, and flight-test to take capabilities from prototype to sim to HITL to flight to deployment.

Skills

Python for ML

C++ on Linux

PyTorch

Edge deployment

MLOps

Multi-GPU training

Education

BS/MS/PhD in CS/EE/Robotics

Tools

TensorRT

ONNX Runtime

ROS 2

Jetson platforms

CUDA

Job description

Mach Industries is building an AI-forward autonomy stack for contested environments where GPS sensing is unreliable. As a Machine Learning Engineer, you will own and scale the training, data, and edge-inference backbone that every vision and multi-sensor model on our product lines depends on for detection, tracking, search, navigation, and ATR.

This high-ownership role spans data infrastructure, model training, and deployment on embedded hardware in flight.