Machine Learning Engineer (AI)

Location: Huntington Beach, California, United States; on-site

Salary: $120,000–$160,000 per year, plus equity

Company

hirify.global is a defense technology startup developing autonomous defense platforms and decentralized systems for the United States and its allies.

What you will do

• Own and scale training and data infrastructure for flight, simulation, and hardware-in-the-loop data, including curation, labeling, QA, versioning, and reproducible dataset builds.
• Build distributed multi-GPU training, experiment tracking, model registry, CI-based evaluation, and automated retraining-to-deployment workflows.
• Deploy and optimize detection, segmentation, tracking, search, classification, and multi-sensor fusion models for real-time inference on Jetson-class hardware.
• Generate synthetic data through simulation and domain randomization to improve long-tail coverage and sim-to-real transfer.
• Implement runtime health monitoring, drift detection, graceful degradation, and model-performance feedback loops.
• Collaborate with perception, localization, embedded, and flight-test disciplines to move capabilities from prototype through simulation, hardware-in-the-loop, flight testing, and deployment.

Requirements

• Strong software engineering skills in Python and production C++ on Linux, including profiling, optimization, and rigorous testing.
• Experience building end-to-end ML data and training pipelines with dataset construction, labeling and QA, augmentation, experiment tracking, and reproducible training.
• Hands-on PyTorch training and fine-tuning across modern CNN- and Transformer-based detection, segmentation, and tracking architectures.
• Experience with model compression and real-time edge deployment using INT8/FP16, TensorRT or ONNX Runtime, and embedded GPU hardware.
• Experience with SQL or Parquet, dataset versioning, CI-based validation, and scalable multi-GPU training.
• BS, MS, or PhD in computer science, electrical engineering, robotics, or a related field, or equivalent experience; production or hardware deployment experience is required. Employment requires authorization to work in the United States and may require eligibility under U.S. export-control regulations without sponsorship for an export license.

Nice to have

• Synthetic data generation and simulation using tools such as Unreal or Isaac, with demonstrated sim-to-real transfer.
• EO/IR imagery, flight-test data, multi-modal perception, and fusion of radar, LiDAR, or RF data.
• CUDA performance debugging, ROS 2, NVIDIA Jetson deployment pipelines, drift monitoring, rare-event testing, and long-horizon reliability metrics.
• Distributed training frameworks, cloud ML platforms such as SageMaker, Docker, or Rust systems tooling.

Culture & Benefits

• Startup-scale environment focused on rapid manufacturing, autonomy, innovation, and national security.
• Equity or stock options included in most offers.
• Health, dental, and vision insurance, retirement savings, and paid time off.
• Funding for continuing education, training, and professional development.
• Employment authorization is verified through E-Verify and Form I-9.