Design, prototype, test, and deploy mechanical subsystems for warehouse robots across the full hardware lifecycle. Collaborate with industrial design, electrical engineering, product, and software teams; resolve system issues; manage vendors; and execute test plans for robotic designs.
About you and this role:
Robust AI is a fast-growing, early-stage startup founded in 2019 by an unsurpassed team of veterans in robotics, AI and business. We are a collaborative group with a wide range of backgrounds and perspectives, seeking talented individuals who are just as excited about robotics and AI as we are! Help us redefine the very foundation of robotics and build robots that are smart, collaborative, robust, safe, flexible and genuinely autonomous.
As a mechanical engineer at Robust AI you will join a small fast-paced team working to design and deploy the next generation of warehouse robotic systems. Working with the other engineers on the team you will help concept, design, build and test subsystems of our robot. You are someone who is excited about seeing robots deployed at a large scale. You are someone who is comfortable working in an early stage startup environment and are able to pivot effectively. The base pay range for this role is between $150,000 and $200,000, dependent on your skills, qualifications and experience.
Main responsibilities:
- Work with the mechanical team to deliver the next generation design of our robot
- Design and manage components across the HW lifecycle (concept, design, fabrication, test, production)
- Engage cross functionally with industrial design, electrical engineering, product and software to make sure design decisions fit within the constraints of the system
- Propose and resolve issues with current robot systems while accounting for engineering effort and budget
- Rapidly iterate on design by building quick prototypes
- Design and execute test plans for your designs
What you’ll bring to the table:
- 5+ years of industry experience and BS in Mechanical Engineering or equivalent
- Proficiency in SolidWorks & PDM
- Background in user-facing product design
- Ability to communicate effectively cross-functionally
- Hands-on work with robotic or mechatronic systems
- Ability to work independently
- Track record of working with and managing vendors
What we offer:
- Base pay between $150,000 and $200,000, dependent on your skills, qualifications and experience.
- Stock options and huge potential for growth.
- Strong startup (and fun) culture.
- Medical, Dental, and Vision coverage.
- Flexible vacation and sick leave practices.
- Paid parental leave.
Robust AI fosters a culture of belonging and a shared commitment to equality and equity. Having a diverse set of perspectives is key to ensuring AI and robotics serve the needs of all.
Robust.AI San Carlos, California, USA Office
1050 Commercial St,, San Carlos, CA, United States, 94070
Similar Jobs
Artificial Intelligence • Cloud • Information Technology • Consulting
Leads mechanical design, structural FEA, analysis, testing, and qualification of complex networking systems from concept through production. Responsibilities include chassis and fixture design, simulation-to-test correlation, dynamic testing, tolerance analysis, root-cause investigations, manufacturing support, and corrective action implementation. The role collaborates with ASIC, hardware, manufacturing, suppliers, and cross-functional engineering teams while ensuring structural integrity, reliability, manufacturability, and regulatory compliance.
Top Skills:
3D-Scanning MetrologyAccelerometersAnsys WorkbenchAstm D4169CadEcad-Mcad IntegrationEmcEmiEpdmFeaGd&TGr-63HaltIdf WorkflowsIpc-9704Ls-DynaMdvtNebsSolidworksStrain Gauges
Artificial Intelligence • Hardware • Software • Nanotechnology • Semiconductor • Quantum Computing • Defense
Lead the design, development, qualification, and production of infrared detector packaging, cold stages, Integrated Dewar Assemblies, cryogenic hardware, and precision electromechanical systems. Perform thermal, structural, tolerance, and reliability analyses; create CAD models, drawings, specifications, bills of materials, and documentation; apply GD&T; support environmental and qualification testing; participate in customer and design reviews; and provide technical mentorship.
Top Skills:
3D CadAs9100Cryogenic HardwareGd&TInfrared Detector PackagingIntegrated Dewar Assemblies (Idas)Reliability AnalysisStructural AnalysisThermal AnalysisTolerance Analysis
Aerospace • Information Technology • Software • Cybersecurity • Design • Defense • Manufacturing
Designs, analyzes, integrates, and sustains aircraft mechanical systems, primarily C-17 Environmental Control Systems. Responsibilities include developing drawings and specifications, supporting reviews, resolving field issues through root cause analysis, coordinating suppliers, communicating with Air Force customers, mentoring engineers, and leading small teams. The role requires occasional travel to supply chain locations and military bases.
Top Skills:
TeamcenterUnigraphics Nx
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
