Machine Learning Software Engineer
Posted 8 Oct 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 3+ yrs
- Management level
- Individual contributor
- Employment
- On-Site
- Contract
- Full-time
No salary listed for this role.
Field of studyArtificial Intelligence, Computer Engineering, Computer Science, Electrical Engineering, Machine learning, Mathematics, Mechanical Engineering, Robotics (or related)
Study levelBachelor's
Foundational Industries · SF Bay Area · Full-Time
About Foundational
Foundational is building a network of AI-native, autonomous factories for modern contract manufacturing, reshoring critical supply chains so companies can produce high-quality products domestically, quickly, and at competitive cost. Recent breakthroughs in robotics and physical AI have shifted autonomous manufacturing from theoretical to deployable, and we’re focused on operationalizing these capabilities at scale during a decisive decade for American industrial leadership.
WHO — Who Thrives Here
This role is for a Machine Learning Software Engineer who will design, develop, test, and deploy software systems for advanced robotic and autonomous platforms used in industrial and automation environments. The role involves working on motion planning, kinematics, perception, and real-time control systems to enable robust, autonomous robotic operations.
A note on pace: this is a startup building something genuinely hard. The people who do best here bring a sense of urgency that’s internal, not installed. If you need the environment to create pressure for you, this probably isn’t the right fit. If you’re the one creating pressure for the environment, keep reading.
MISSION
Build the software systems that power Foundational’s AI-native manufacturing platform, from first principles to production.
OUTCOMES — What Success Looks Like in 6–12 Months
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Software Development: Design, implement, and maintain scalable software architectures and real-time control systems for robotic platforms using C++ and/or Python.
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Perception Pipelines: Build and integrate perception software, including computer vision, depth sensing, and point cloud processing, to enable robotic systems to interpret dynamic environments.
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Algorithm Implementation: Write, optimize, and validate motion planning and kinematics algorithms for tasks such as object manipulation, path planning, obstacle avoidance, and multi-axis motion control.
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System Integration: Integrate robotic software with physical hardware, sensors, actuators, programmable logic controllers (PLCs), and standard industrial communication protocols.
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Simulation & Testing: Build, maintain, and utilize simulation environments to test, validate, and benchmark robotic behaviors and control algorithms prior to physical deployment.