Senior ML/AI Engineer — Edge Vision for Mission AR

HEADBORNE.AI; Columbus (GA); On-site; USD 125,000 - 190,000; Full time

Benefits offered by this job

Stock options

Job summary

HEADBORNE.AI in Columbus, GA seeks a Senior ML Engineer to develop ML solutions for advanced sensor tech from concept to deployment, optimizing object detection and image enhancement on embedded platforms.

You will lead data pipelines, drive low-latency inference, and integrate models into AR helmets, drones, and robots while collaborating with hardware and software teams to meet mission-based safety goals.

Qualifications

• MS or PhD in Computer Science or related field.
• 2+ years shipping production-grade ML systems.
• Deep expertise in ML algorithms and applied computer vision.
• Proficiency in Python and PyTorch.
• Experience across full ML lifecycle: data curation, training, evaluation, deployment.
• Ability to optimize models for real-time performance on edge platforms.

Responsibilities

• Own and lead the development of ML models for object detection, tracking, and image enhancement on embedded platforms.
• Build and maintain scalable data pipelines for sensor data ingestion, training, and evaluation.
• Optimize inference performance for low-latency edge compute environments.
• Integrate ML models into mission-critical systems for AR helmets, drones, and robotic platforms.
• Conduct experiments and benchmarking across diverse imaging conditions and sensor types.
• Collaborate with software and hardware teams to align ML architecture with embedded constraints.
• Contribute to code quality, reproducibility, and CI/CD for ML pipelines.
• Explore and prototype new ML applications aligned with HEADBORNE’s mission.

Skills

ML algorithms

Computer vision

Python

PyTorch

Edge deployment

Education

MS or PhD in Computer Science

Job description

HEADBORNE.AI in Columbus, GA seeks a Senior ML Engineer to develop ML solutions for advanced sensor tech from concept to deployment, optimizing object detection and image enhancement on embedded platforms.

You will lead data pipelines, drive low-latency inference, and integrate models into AR helmets, drones, and robots while collaborating with hardware and software teams to meet mission-based safety goals.