Gradient Robotics Logo

Gradient Robotics

Founding Software Engineer

Reposted One Month Ago
Be an Early Applicant
In-Office
Menlo Park, CA, USA
Senior level
In-Office
Menlo Park, CA, USA
Senior level
Build and ship performance-critical, low-latency software that interfaces with robot hardware. Own end-to-end data and inference pipelines, optimize latency and determinism, and work across kernel/firmware to autonomy stack with real robots.
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 own and build our full robotics stack — designing the hardware, building the software systems, training ML models, and manufacturing through a global supply chain — for world-class iteration speed, reliability, and scale.

We've built 3 generations of robots 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 and built the best-selling open-source humanoid robots in the US at K-Scale Labs and worked on generations of foundation software for Tesla Optimus.

The Role

As a founding software engineer at Gradient, you'll work close to the hardware — from kernel and firmware up to the autonomy stack. You'll own data pipelines that move hundreds of megabytes at single-digit millisecond latency. Your systems will bring visibility and determinism into real-time, end-to-end inference pipelines with one goal: the ML model is the only stochastic component.

What You'll Do
  • Ship performance-critical code to real robots daily

  • Understand the full data flow from AI models all the way to actuators

  • Push down latency and tighten the stack to make the system faster, more deterministic, and more reliable

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

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

  • Firmware / Platform: Linux kernel hacking, embedded systems

Nice to Have
  • Tracing / Profiling: ftrace, flamegraphs, eBPF

  • Linux I/O: DPDK, SPDK, io_uring

You're a Fit If You've:
  • Shipped production systems close to hardware (drivers, kernels, embedded, robotics, or similar)

  • Debugged timing and concurrency issues in the wild

  • Owned messy, ambiguous problems and turned them into robust software

At Gradient, you’ll ship performance-critical code to real robots daily, understand the full data flow from AI models all the way to actuators, and watch the system get faster, more deterministic, and more reliable as you push down latency and tighten the stack. If that excites you, we should talk.

Similar Jobs

Yesterday
In-Office or Remote
San Francisco, CA, United States
190K-270K Annually
Senior level
190K-270K Annually
Senior level
Artificial Intelligence • Software • Biotech • Pharmaceutical
Build and operate production AI systems for FDA regulatory intelligence, including evaluation pipelines, document ingestion and retrieval, multi-agent workflows, data pipelines, cloud infrastructure, and secure multi-tenant services. Collaborate with former FDA experts to translate domain judgment into product requirements and evaluation cases. Own architecture, reliability, observability, cost, security, and rapid 0-to-1 delivery across the stack.
Top Skills: AlembicAmazon EcrAmazon RdsAmazon S3Anthropic ApiApplication Load BalancerAws EcsAws FargateAws Secrets ManagerClaude Agent SdkCloudflareDockerFastapiGithub ActionsGraphragKnowledge GraphsLanggraphMcpOpentofuPostgresPymupdfPythonPython-DocxReactSQLSqlalchemyTailwind CssTerraformTypescriptVercel Ai SdkVite
2 Days Ago
In-Office
San Francisco, CA, USA
170K-230K Annually
Junior
170K-230K Annually
Junior
Professional Services • Consulting
Own the full-stack product and AI engineering, building backend services, data storage, APIs, application layers, real-time media pipelines, and AI workflows from prototype to production. Develop evaluation tooling, internal automation, and hardware integrations while operating as a backend-leaning generalist. Collaborate with founders, support go-to-market decisions, and help recruit engineers. The role requires on-site work five days per week in San Francisco.
Top Skills: AIAPIsCloud PlatformsComputer VisionDatabasesDevice SdksEdge InferenceEmbedded LinuxEmbedded SystemsFirmwareLow-Latency StreamingMultimodal AiReal-Time Media Pipelines
2 Days Ago
In-Office
San Francisco, CA, USA
130K-180K Annually
Entry level
130K-180K Annually
Entry level
Professional Services • Consulting
Build and launch production AI services, including agent-style workflows and retrieval pipelines, for external business customers. Design data models and scalable pipelines, own products from concept through launch, and collaborate with commercial teams and customers. Use customer feedback to improve the platform rapidly. The role requires production LLM experience, startup or zero-to-one ownership, strong Python or equivalent programming skills, database design knowledge, and understanding of distributed systems.
Top Skills: Agent WorkflowsAi ServicesData PipelinesDatabasesDistributed SystemsLarge Language ModelsPythonRetrieval Pipelines

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