Senior Computer Vision ML Engineer - Edge Perception

Anduril-1; Irvine (CA); On-site; USD 220,000 - 292,000; Full time

Job summary

Anduril Industries in Irvine, CA is seeking a Machine Learning Engineer to own the full ML stack for the Counter Intrusion team. You will design and train multi-sensor object detection models for edge devices and develop learning algorithms to optimize autonomous systems.

You will also build end-to-end data collection and training infrastructure, deploy real-time ML pipelines, and mentor junior engineers while collaborating with camera, systems, and labeling teams.

Qualifications

• MS or PhD with emphasis on Computer Vision or ML.
• style:standard
• BS in related field with strong ML basics.
• style:standard
• 6+ years building ML algorithms on large datasets.
• style:standard
• Proficient in deep learning frameworks (PyTorch, TF, JAX).
• style:standard
• Experience deploying models with TensorRT and ONNX.
• style:standard
• Strong on-device inference and CV model deployment.

Responsibilities

• Own the ML stack for the Counter Intrusion team.
• style:standard
• Design and train multi-sensor object detection models.
• style:standard
• Develop learning algorithms for autonomous systems.
• style:standard
• Build end-to-end ML infrastructure for data collection & training.
• style:standard
• Prototype and deploy real-time ML pipelines.
• style:standard
• Mentor junior ML engineers and collaborate cross-functionally.

Skills

Deep Learning

Computer Vision

C++

Python

Linux

CI/CD

Edge Inference

Model Deployment

Latency Optimization

On-device AI

Education

MS/PhD in ML/CS/Robotics

BS in CS/ML/EE

Tools

PyTorch

TensorFlow

JAX

ONNX

TensorRT

Linux

Job description

Anduril Industries in Irvine, CA is seeking a Machine Learning Engineer to own the full ML stack for the Counter Intrusion team. You will design and train multi-sensor object detection models for edge devices and develop learning algorithms to optimize autonomous systems.

You will also build end-to-end data collection and training infrastructure, deploy real-time ML pipelines, and mentor junior engineers while collaborating with camera, systems, and labeling teams.