Platform Engineers at Bright Machines are responsible for defining and implementing the systems that make Software Defined Manufacturing possible and that power our flexible robotic manufacturing lines. Our robots, and the software that controls them, are deployed in a variety of factory conditions and help support the manufacturing operations for some of the biggest names in the industry.
As a Senior Platform/MLOps Engineer, you will build scalable systems that are foundational to the Bright Machines technology stack. With a focus on our AI/ML infrastructure, you will design, implement, and maintain our training pipelines, model deployments, and inference app workloads. Our computer vision and deep learning models are used for defect detection, classification, and visual validation, providing end-to-end inspection solutions that deliver consistent, accurate results under real-world factory conditions. You will collaborate with the Smart Robotics team and the Platform Engineering team to design, implement, and deploy our GPU workloads in kubernetes. If you are ready to apply exceptional engineering practices and build the platform that will define the next generation in manufacturing, this is your opportunity to “Be Bright”.
WHAT YOU WILL BE DOING
Design, implement, and maintain reliable, scalable, and secure infrastructure, applications, and tooling, with a focus on our ML/AI pipelines and workloads
Write clean, maintainable code, and perform peer code-reviews
Write clear and concise documentation and engage in cross-team communication and knowledge sharing
Work with other team members to investigate design approaches, prototype new technology and evaluate technical feasibility
Pair with adjacent teams to understand how your frameworks and infrastructure are actually used in the field, continuously improving them and leveraging recent advances to improve developer velocity
WHAT YOU WILL BRING
At least 5+ years of experience in Platform Engineering, DevOps, or Site Reliability Engineering (SRE).
B.S. or M.S. degree (or equivalent) in Computer Science, Engineering, or a related field
Proficiency in at least one modern programming languages (Python, Javascript, C#, Go, etc)
Demonstrated industry best-practices in MLOps
Proficiency with CI/CD tools and GitOps workflows
Familiarity with running GPU workloads in kubernetes
Strong knowledge of Kubernetes (self-hosted and managed) and modern k8s paradigms (e.g. CNCF)
Proficiency with Infrastructure as Code tools (Terraform, etc) and configuration management tools (Ansible, etc)
Familiarity with observability stacks (Prometheus, Grafana, OpenTelemetry)
- Travel 25%
IT WOULD BE GREAT IF YOU HAD
Experience in air-gapped or extremely strict security environments
Experience communicating with users, technical leaders and management to collect requirements, describe system designs, and architecting software systems that meets your stakeholders needs
Knowledge and demonstrated application of software engineering best practices relating to the SDLC including code reviews, SCM, CI/CD, testing, and operations
Demonstrated ability to mentor and grow other team members
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.
Skills Required
- At least 5+ years of experience in Platform Engineering, DevOps, or Site Reliability Engineering (SRE)
- B.S. or M.S. degree in Computer Science, Engineering, or a related field
- Proficiency in at least one modern programming languages
- Demonstrated industry best-practices in MLOps
- Proficiency with CI/CD tools and GitOps workflows
- Familiarity with running GPU workloads in kubernetes
- Strong knowledge of Kubernetes and modern k8s paradigms
- Proficiency with Infrastructure as Code tools and configuration management tools
- Familiarity with observability stacks
What We Do
We deliver intelligent, software-defined manufacturing by bringing together our flexible factory robots with intelligent software, production data and machine learning. Our growing, global team of more than 300 robotics, software and manufacturing industry veterans believe building physical things should be as seamless and simple as creating digital products. Our software-defined manufacturing platform helps customers innovate faster to meet the growing demands of a new era of manufacturing.
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