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Description

Senior Robot Perception Engineer - Smart Robotics

Team: Software Engineering

Location: San Francisco, California

Commitment: Full time Exempt

Workplace Type: hybrid

RETHINK MANUFACTURING

The only way to ignite change is to build the best team. At Bright Machines®, we’re innovators and experts in our craft who have joined together to create a new category of manufacturing that will help transform the industry. We believe software and data are the answer, thoughtfully applied to solve our customers’ unique challenges. Through intelligent automation, we give factories newfound flexibility, scalability, and resilience. We deliver products to meet the demands of today while building a platform to take advantage of what comes next.

Working with us means you’ll have the opportunity to make lasting, impactful changes for our company and our customers. If you’re ready to apply your exceptional skills to create the factory of the future, we’d love to speak with you.

ABOUT THE ROLE

As a senior Robot Perception Engineer on the Smart Robotics team at Bright Machines, you will be a hands-on senior contributor responsible for productizing visual inspection solutions for our automation platform. You will own the full pipeline—from algorithm development to production deployment—turning prototype inspection capabilities into reliable, high-throughput features that operate at scale across our automation lines. In this role, you will develop and optimize computer vision and deep learning models for defect detection, classification, and visual validation. You will collaborate closely with cross-functional teams, including Mechanical Engineering and Manufacturing Operations, to design end-to-end inspection solutions that deliver consistent, accurate results under real-world factory conditions. Additionally, you will have the opportunity to shape the inspection product roadmap and drive the adoption of cutting-edge machine learning techniques in an industrial setting.

WHAT YOU WILL BE DOING

Develop and optimize visual inspection algorithms for defect detection, anomaly detection, classification, and quality validation using deep learning
Optimize model inference for GPU deployment, leveraging CUDA, TensorRT, and related acceleration frameworks
Collaborate with Mechanical engineers to design illumination setups that maximize inspection accuracy and robustness
Build and maintain data pipelines for model training, evaluation, and continuous improvement
Partner with platform team to establish MLOps practices for model versioning, experiment tracking, automated retraining, and production model monitoring
Harden inspection solutions for production reliability, including monitoring, alerting, and graceful degradation
Work with service engineering and field teams to deploy inspection solutions and support customer rollouts
Define metrics and benchmarks to measure inspection accuracy, throughput, and reliability

WHAT YOU WILL BRING

MS or PhD in Computer Science, Electrical Engineering, or a related field, or the equivalent in experience with evidence of exceptional ability.
5+ years of relevant experience in computer vision and/or machine learning
Strong programming skills in Python
Deep experience with PyTorch for model development and training
Experience optimizing ML models for GPU inference in production environments
Track record of shipping ML/CV models from prototype to production
Experience with image acquisition, camera systems, and sensor integration

IT WOULD BE GREAT IF YOU HAD

Knowledge of lighting and optics for machine vision (diffuse/directional illumination, lens and filters)
Experience with industrial camera systems and standards (GigE Vision, GenICam, CoaXPress)
C/C++ experience for performance-critical components
Experience with MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar)
Experience with data annotation, labeling workflows, and active learning strategies
Experience with ROS2
Understanding of manufacturing processes and quality control methodologies
Publications or patents in computer vision, deep learning, or related fields

BE EMPOWERED TO CHANGE AN INDUSTRY

Bright Machines is a next-generation, AI-enabled manufacturer focused on data center infrastructure assembly operations. Bright Machines uses its proprietary AI-based robotics and software to assemble AI infrastructure hardware products (i.e., data center servers) for hyperscalers and leading Original Equipment Manufacturers (OEMs). With its new AI factory, Bright Machines addresses increasing market demands for computing power due to the surge of AI and the U.S. national mandate to reshore manufacturing by building data center infrastructure at scale with higher quality and shorter time-to-market.

Bright Machines is headquartered in San Francisco, California, with an integration center in Guadalajara, Mexico. The company has been recognized as one of Forbes’ AI 50, awarded “Best AI-based Solution for Manufacturing” by AI Breakthrough, named a “Technology Pioneer” by the World Economic Forum, and highlighted by several other leading technology and innovation organizations.

Bright Machines

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Frequently Asked Questions

We prioritize job seekers as our customers, unlike bigger job sites, by charging a small fee to provide them with curated access to the best companies and up-to-date jobs. This focus allows us to deliver a more personalized and effective job search experience.
We've got over 200,000 jobs from 15,000+ vetted companies. No fake or sleazy jobs here!
We aggregate jobs from 15,000+ companies' career pages, so you can be sure that you're getting the most up-to-date and relevant jobs.
We're the only job board *for* software engineers, *by* software engineers… in case you needed a reminder! We add thousands of new jobs daily and offer powerful search filters just for you. 🛠️
Every single hour! We add 2,000-3,000 new jobs daily, so you'll always have fresh opportunities. 🚀
Typically, job searches take 3-6 months. EchoJobs helps you spend more time applying and less time hunting. 🎯
Check daily! We're always updating with new jobs. Set up job alerts for even quicker access. 📅

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