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About the Role
Mach Industries is building an AI-forward autonomy stack for contested environments. As a Machine Learning Engineer, you will own and scale the training, data, and edge-inference backbone for all vision and multi-sensor models, enabling rapid iteration and real-time deployment on embedded hardware.
Responsibilities
- Own and evolve the training and data infrastructure: ingestion, curation, labeling/QA, dataset versioning, and reproducible builds.
- Stand up and scale training/eval infrastructure: distributed multi-GPU training, experiment tracking, model registry, and CI-based evaluation.
- Deploy and optimize models for real-time edge inference on Jetson-class hardware, meeting latency, throughput, and SWaP targets.
- Build and improve models including detection, segmentation, tracking, search, classification/ATR, and multi-sensor fusion.
- Generate and manage synthetic data at scale for long-tail coverage and sim-to-real transfer.
- Instrument runtime health, drift detection, graceful degradation, and feedback model performance to the retraining loop.
- Develop tooling for visualization, triage, and root-cause analysis of flight data.
- Partner with other autonomy disciplines to transition capabilities from prototype to deployment.
Requirements
- Strong generalist software engineering: Python for ML and tooling, production C++ on Linux, profiling, optimization, and rigorous testing.
- Proven experience building ML data and training pipelines end-to-end.
- Hands-on training and fine-tuning in PyTorch across modern detection/segmentation/tracking architectures.
- Edge and real-time deployment experience with model compression and runtime optimization on embedded GPU hardware.
- Experience with Data and MLOps infrastructure: SQL/Parquet, dataset/versioning tools, CI-based validation, and scalable multi-GPU training.
- BS/MS/PhD in CS/EE/Robotics or equivalent experience, with a track record of shipping ML models to production or hardware.
- Senior candidates should have deeper ownership of training/data infrastructure at scale.
- Must be a U.S. citizen or national, U.S. lawful permanent resident, refugee, or asylee, or eligible for required U.S. Department of State authorizations.
Skills
- Python
- C++
- PyTorch
- TensorRT
- ONNX Runtime
- DVC
- Parquet
- SQL
- CUDA
- ROS 2
- NVIDIA Jetson
- Docker
- Rust
- Unreal/Isaac
- Domain randomization
- Sim-to-real transfer
- EO/IR imagery
- Multi-modal perception
- Feature fusion
- Decision fusion
- Active learning
- Data-mining
- Drift/dataset-shift monitoring
- Robustness testing
- Rare-event testing
- Long-horizon reliability metrics
- Distributed training
- Cloud ML platforms (e.g. SageMaker)
Location
- Remote
- Onsite
Work Type
- Full-time
Experience Level
- Engineer
- Senior Engineer
Education Level
- BS/MS/PhD in CS/EE/Robotics or equivalent experience
Salary/Compensations
- $120,000—$160,000 USD (Engineer)
- $165,000—$220,000 USD (Senior Engineer)
Benefits
- Healthcare
- Dental
- Vision plans
- Retirement savings
- Paid time off
- Continuing education funds
- Training funds
- Career growth funds
- Competitive Salaries
- Performance-Based Incentives
- Equity Participation
- Stock options
About the Company
- Mach Industries is a rapidly growing defense technology company founded in 2023, focused on developing next-generation autonomous defense platforms.
- The company's mission is to deliver scalable, decentralized defense systems that enhance the strategic capabilities of the United States and its allies.
- With approximately 350 employees, Mach Industries operates with startup agility and ambition.
- The vision is to redefine the future of warfare through cutting-edge manufacturing, innovation at speed, and unwavering focus on national security.
- Mach Industries is dedicated to solving the next generation of warfare with lethal systems that deter kinetic conflict and protect global security.
Equal Opportunity
- Mach is an equal opportunity employer committed to creating a diverse and inclusive workplace. All qualified applicants will be treated with respect and receive equal consideration for employment without regard to race, color, creed, religion, sex, gender identity, sexual orientation, national origin, disability, uniform service, Veteran status, age, or any other protected characteristic per federal, state, or local law, including those with a criminal history, in a manner consistent with the requirements of applicable state and local laws.