Machine Learning Engineer

UnitX•Milpitas, CA

42d•$170,000 - $200,000

About The Position

UnitX builds the world's leading physical AI systems to automate repetitive visual tasks in factories. UnitX is a fast-moving startup with a team from Stanford, MIT, Google, and beyond. Since inception, UnitX has deployed 1,000+ mission-critical systems across 190+ of the world's leading manufacturers' production lines. Every year, $15B worth of products go through UnitX's AI inspection system to ensure quality. Join us for the rare opportunity to work on computer-vision-driven products that go beyond the state of the art and that improve global manufacturing efficiency.

Requirements

Bachelor's degree (or foreign equivalent) in Computer Science, Mathematics, Statistics, or a closely related discipline.
3+ years of experience in the job offered or a related occupation.
3+ years of hands-on experience in Deep Learning & Neural Networks
3+ years of hands-on experience in Machine Learning Pipeline Development
3+ years of hands-on experience in Sensor Fusion & Signal Processing
3+ years of hands-on experience in Computer Vision & Real-Time Inference Optimization
3+ years of hands-on experience in Statistical Modeling & A/B Testing

Responsibilities

Design, train, and optimize deep learning models for defect detection and segmentation using high-resolution images and 3D sensor inputs.
Implement advanced computer vision techniques (including Stable Diffusion, Segment Anything Model (SAM), and transformer-based architectures) to ensure pixel-level precision and real-time inference.
Develop and maintain automated pipelines for data preprocessing, augmentation, and model training to continuously optimize deployed solutions.
Develop scalable ML pipelines for deployment on both edge devices and cloud-based systems.
Optimize model inference for real-time decision-making, ensuring processing times remain under 20 milliseconds.
Work closely with software engineers, robotics specialists, and hardware teams to seamlessly integrate ML solutions into fully automated industrial workflows.
Implement automated monitoring and alerting systems to track model drift, identify failures, and ensure 24/7 fault tolerance in a manufacturing environment.
Create frameworks to assess model accuracy, precision, recall, and efficiency.
Design visualization dashboards, conduct A/B testing, and leverage explainable AI (XAI) to improve transparency in quality assurance.
Investigate emerging AI/CV techniques, including self-supervised learning, domain adaptation, and multimodal data fusion.
Develop novel architectures incorporating reinforcement learning and Generative AI, and contribute to academic publications, patents, and open-source projects.