Machine Learning Engineer

About this role

Mach Industries seeks a Machine Learning Engineer to design and scale the training, data, and edge-inference infrastructure powering autonomous defense systems. You'll own the full ML pipeline—from data ingestion and curation to model deployment on embedded hardware—enabling real-time vision and multi-sensor autonomy in GPS-denied environments.

What you'll do

• Build and maintain training/data pipelines: ingestion, curation, labeling workflows, dataset versioning, and reproducible builds
• Scale distributed multi-GPU training, experiment tracking, model registry, and CI-based evaluation with automated retraining loops
• Deploy and optimize computer vision models for real-time edge inference on Jetson hardware using quantization, TensorRT, and ONNX Runtime
• Train and improve detection, segmentation, tracking, and multi-sensor fusion models across the product portfolio
• Generate and manage synthetic data at scale to cover edge cases and close sim-to-real gaps
• Monitor runtime performance, detect dataset drift, and instrument health metrics to feed back into retraining loops

What they're looking for

• Python (ML and tooling) and production C++ on Linux
• PyTorch training and fine-tuning for modern architectures (CNN, Transformer, detection/segmentation)
• Edge model optimization: INT8/FP16 quantization, TensorRT, ONNX Runtime, Jetson deployment
• ML data pipeline design: dataset construction, labeling, augmentation, experiment tracking
• MLOps and infrastructure: SQL, Parquet, DVC, distributed training, CI/CD validation
• Synthetic data generation and simulation (Unreal, Isaac, domain randomization)
• EO/IR imagery and multi-modal sensor fusion
• Performance profiling and optimization on embedded GPU hardware