Real-Time Edge AI Engineer for Autonomous Systems

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

Benefits offered by this job

Healthcare

Equity participation

Professional development

Paid time off

Job summary

Mach Industries is seeking a Machine Learning Engineer to own the data and training infrastructure for our AI-forward autonomy stack. You will build scalable pipelines, manage synthetic data, and deploy real-time edge models on Jetson-class hardware.

We expect strong expertise in ML data engineering, Python/C++, and experience with PyTorch, distributed training, and model optimization. This role offers high ownership in a mission-focused hardware environment.

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, curation and mining, labeling/QA workflows, dataset versioning (DVC/Parquet), 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 plus automated field-data to retrain to validate to redeploy loops.
• Deploy and optimize models for real-time edge inference on Jetson-class hardware (quantization/pruning, TensorRT/ONNX Runtime); profile CPU/GPU and hit 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 for EO/IR and auxiliary sensing.
• 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 the data and retraining loop.

Skills

Python for ML

C++ on Linux

PyTorch

ML data pipelines

CI/CD / MLOps

Education

BS/MS/PhD in CS/EE/Robotics or equivalent

Tools

DVC/Parquet

TensorRT/ONNX Runtime

CUDA

ROS 2

NVIDIA Jetson

Job description

Mach Industries is seeking a Machine Learning Engineer to own the data and training infrastructure for our AI-forward autonomy stack. You will build scalable pipelines, manage synthetic data, and deploy real-time edge models on Jetson-class hardware.

We expect strong expertise in ML data engineering, Python/C++, and experience with PyTorch, distributed training, and model optimization. This role offers high ownership in a mission-focused hardware environment.