Gradient Robotics Logo

Gradient Robotics

Founding Engineer (Extraordinary Ability)

Reposted One Month Ago
Be an Early Applicant
In-Office
San Francisco, CA, USA
Senior level
In-Office
San Francisco, CA, USA
Senior level
Join as a founding engineer (Mechanical, ML, or Software) to design and ship hardware, models, and low-latency software to real robots daily. Make long-lasting design decisions, iterate rapidly, and deploy production systems across the full robotics stack.
The summary above was generated by AI
About Gradient Robotics

Gradient Robotics is building intelligent robots for data centers and factories. We believe the fastest practical path to capable general-purpose robotics is through industry deployment. We're here to change the world with robotics.

We own and build our full robotics stack: designing the hardware, building the software systems, training ML models, and manufacturing through a global supply chain, all for world-class iteration speed, reliability, and scale.

We've built 3 generations of robots in 4 months with a team of 7, backed by top-tier investors and working toward pilots with the world's largest data center builders. Our team created the best-selling open-source humanoid robots in the US at K-Scale Labs and shipped foundation software at Tesla Optimus and Google.

The Role

This is a dedicated track for engineers and researchers with extraordinary records who want to stay in the US long-term. Gradient Robotics will file an O-1A petition with top immigration firms on your behalf. Our founders have been through the process ourselves.

These positions require extraordinary technical capability: novel mechanism design, frontier robot learning, or systems performance at the edge of what's currently possible. Founding engineers here make decisions the company will live with for years.

You'll join as a founding engineer in one of three focus areas:

Mechanical. Own the robot end-to-end: analyze payload capacity and kinematics, design mechanisms that are nimble and safe, and take ideas from multi-physics simulation to the last deburred sheet-metal edge.

ML. Train and deploy the models that make our robots useful in the real world. Work across the full pipeline: data collection, VLA pre-training, fine-tuning, and RL-based self-improvement on real hardware.

Software. Work close to the hardware, from kernel and firmware up to the autonomy stack. Own data pipelines that move hundreds of megabytes at single-digit millisecond latency.

Across every track, your work ships to real robots daily.

What You'll Do
  • Make hard design decisions the company will live with for weeks, sometimes months

  • Ship code, mechanisms, or models to real robots running in real environments

  • Move fast, iterate hard, and watch your work compound across robot generations

Required Background

Strength in one of these focus areas:

Mechanical

  • Mechanical Design: Precision mechanisms, structures, actuators, DFMA

  • Analysis: Multi-physics simulation, FEA, tolerance stacks, vibration/thermal reasoning

  • Build + Iteration: Prototyping, test rigs, failure analysis, rapid CAD-to-hardware cycles

ML

  • Deep Learning: PyTorch or JAX, distributed training, mixed precision

  • Robot Learning: Imitation learning, diffusion policies, flow matching, or VLA architectures (π₀, OpenVLA, ACT, RT-X, Octo, etc.)

  • Reinforcement Learning: Sim-to-real transfer, distillation

  • Simulation: MuJoCo, Isaac Sim, or Genesis

  • Python: Research-grade code that ships to production

Software

  • Software: Rust, Python, C++, operating systems, multithreading

  • Infrastructure: Bazel, Nix, HIL testing, CI/CD

  • Firmware / Platform: Linux kernel hacking, embedded systems

What "Extraordinary Ability" Means

USCIS requires evidence that you're among the small percentage at the top of your field. Strong candidates typically have several of:

  • Top-tier publications. CoRL, RSS, ICRA, NeurIPS, ICML, ICLR for ML and learning. Equivalent venues for systems, controls, or hardware.

  • Patents. Granted or pending, with you as an inventor.

  • Awards and selections. Best paper, fellowships, competitive prizes, selective programs.

  • Original technical contributions with measurable impact. Open-source projects with significant adoption, production systems shipped at scale, products with real users.

  • Press or media coverage. Coverage of your work in mainstream or trade publications.

  • Peer review or judging. Conference PCs, journal reviewing, hackathon or competition judges.

  • External recognition. High citation counts, invited talks, keynote speaking.

You do not need every category. You do need a credible case. We work with top immigration counsel to assemble the strongest petition possible.

Logistics
  • In-office in San Francisco, CA

  • This role is structured around O-1A classification. Candidates should hold US work authorization with at least 1 year remaining (F-1 OPT, STEM OPT, H-1B, TN, E-3, L-1, or O-1).

  • Available to start imeediately.

If that excites you, apply below.

Similar Jobs

27 Minutes Ago
Hybrid
17-28 Hourly
Junior
17-28 Hourly
Junior
eCommerce • Fashion • Retail • Sales • Wearables • Design
Supervises retail store operations and sales-floor activity, drives sales and KPI performance, develops client relationships, coaches and trains staff, and supports recruiting. Oversees opening and closing procedures, cash handling, POS transactions, inventory accuracy, stockroom organization, replenishment, and omni-channel selling initiatives. Acts as a brand ambassador while maintaining service standards, compliance, and an inclusive team culture.
Top Skills: Clienteling SystemsExcelMicrosoft OutlookMicrosoft PowerpointMicrosoft WordOmni-Channel Selling ToolsPos SystemsSocial Media PlatformsVirtual Selling Tools
2 Hours Ago
In-Office
198K-337K Annually
Expert/Leader
198K-337K Annually
Expert/Leader
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Own chip-level static timing analysis and sign-off for next-generation HBM SoCs through tape-out. Develop SDC constraints, drive timing closure across blocks and full-chip designs, perform MMMC, OCV, signal integrity, and crosstalk analysis, and automate STA workflows using Python and Tcl. Lead post-silicon timing correlation, define sign-off methodologies, communicate risks and readiness, and mentor junior engineers while collaborating across design, verification, physical design, test, and product teams.
Top Skills: 3D IcCadence TempusChipletsDftDramHbmJtagLiberty Timing ModelsMbistPythonSdcSynopsys PrimetimeTclTsv
2 Hours Ago
In-Office
San Jose, CA, USA
154K-303K Annually
Senior level
154K-303K Annually
Senior level
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Define validation strategies, coverage architectures, and scalable methodologies for next-generation data center SSDs. Analyze requirements, architectures, workloads, and validation gaps; develop risk-based coverage models; evaluate emerging technologies; and apply AI, analytics, automation, and LLMs to improve validation effectiveness. Partner across architecture, firmware, systems, product, and validation teams, present strategic recommendations, influence technical direction, and mentor engineers.
Top Skills: Agentic AiAutomationData AnalyticsData Center SsdDual PortEnterprise Storage SystemsFdpFirmwareGenerative AiLarge Language Models (Llms)Machine LearningNandNvmeOcp SsdQlcStorage PerformanceStorage ProtocolsVirtualization

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

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account