Senior ML Engineer, Vision & Autonomy

InvestedintheMission; San Mateo (CA); On-site; USD 163,000 - 245,000; Full time

Job summary

Shield AI is seeking an engineer to develop and deploy advanced ML models for perception in autonomous systems. You’ll own features from development to deployment, collaborating with researchers, perception engineers, autonomy teams and platform engineers.

This role focuses on production-ready ML systems for embedded hardware, using ONNX, TensorRT, and CI pipelines. A SECRET clearance is required; prior defense/customer experience is preferred.

Qualifications

• Typically requires a minimum of 5 years of related experience with a Bachelor’s degree; or 4 years and a Master’s degree; or 2 years with a PhD; or equivalent work experience.
• Proficiency in machine learning fundamentals.
• Experience training and deploying ML models for computer vision in a production setting.
• Strong understanding of 3D vision problems/algorithms.
• Experience with machine learning frameworks such as PyTorch and TensorFlow.
• Demonstrated expertise in deploying models using TensorRT and ONNX.
• Proficiency in C++ and Python.
• Strong analytical and problem-solving skills, with the ability to translate research into practical applications.
• Ability to obtain a SECRET clearance

Responsibilities

• Model Development – Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models that improve perception and decision-making for autonomous systems.
• Data Pipelines & Model Training – Build scalable data pipelines, supervised fine-tuning (SFT) workflows, and evaluation loops that continuously improve model performance on mission-relevant tasks.
• Model Deployment & Optimization – Deploy and optimize machine learning models for embedded hardware using technologies such as ONNX, TensorRT, and hardware-accelerated inference frameworks.
• Perception & Autonomy Applications – Apply modern machine learning techniques to solve challenging perception and autonomy problems across aerial and other autonomous systems operating in complex, real-world environments.
• Research-to-Production – Translate cutting‑edge machine learning research into production-ready capabilities by balancing model performance, robustness, computational efficiency, and operational reliability.
• Cross‑functional Collaboration – Partner closely with perception, autonomy, platform, and software engineering teams to integrate machine learning capabilities into mission‑ready autonomous systems.
• Model Evaluation & Validation – Develop benchmarks, testing methodologies, and evaluation frameworks to measure model performance, identify failure modes, and guide future improvements.
• Continuous Improvement – Improve training infrastructure, developer tooling, deployment workflows, and model lifecycle management to accelerate experimentation and production delivery.

Skills

Machine learning fundamentals

PyTorch

TensorFlow

C++

Python

3D vision

Model deployment

TensorRT

ONNX

Problem solving

Security clearance

Education

Bachelor’s degree; or 4 years + Master’s; or 2 years + PhD

Tools

ONNX

TensorRT

Job description

Shield AI is seeking an engineer to develop and deploy advanced ML models for perception in autonomous systems. You’ll own features from development to deployment, collaborating with researchers, perception engineers, autonomy teams and platform engineers.

This role focuses on production-ready ML systems for embedded hardware, using ONNX, TensorRT, and CI pipelines. A SECRET clearance is required; prior defense/customer experience is preferred.