Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowPosted 191 days ago

Software Engineer, Robotics

Deccan AI13 open roles

Where
San Francisco, CA
Work mode
On site
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowSoftware Engineer, RoboticsDeccan AI · San Francisco, CA

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Deccan AI's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

11.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.3%7 days
  4. 17.6%14 days
  5. 34.3%30 days
  6. 43.5%60 days
This job: posted 191 days ago

The posting

Software Engineer, Robotics & VLA Systems Mountain View, CA · Full-Time · Physical AI Team

About Deccan AI

Deccan AI is a model training and evaluation startup (Mountain View, CA; delivery center in Hyderabad). Founded by IIT Bombay, IIM Ahmedabad, and ex-Google alumni and backed by Prosus Ventures, we build expert-curated datasets and evaluation infrastructure for frontier AI labs including Google DeepMind and Snowflake. Our Physical AI practice is building the data backbone for embodied AI — annotation, synthetic data generation, and model evaluation that help robots learn manipulation and reasoning at scale.

The Role

VLA (Vision-Language-Action) foundation models need more than research breakthroughs — they need production software that connects data pipelines, simulation, training loops, and evaluation into a reliable system. You'll build that system. This is not a pure ML research role or a data engineering role — it sits at the intersection, where you write the code that makes VLA training work end-to-end. You'll work directly with frontier lab clients and ship systems used to train the next generation of robot foundation models.

What You'll Do

  • Build the VLA training integration layer — data loaders, format converters, and preprocessing that feed curated datasets (real + synthetic) into training frameworks (LeRobot, Octo, OpenVLA, π0).
  • Develop evaluation and benchmarking infrastructure: sim-based rollouts in Isaac Lab, success-rate tracking, regression detection, and automated reporting for client delivery.
  • Own dataset management — versioning, schema validation, metadata indexing, and format conversion across Open X-Embodiment, LeRobot HDF5, RLDS, and client-specific formats.
  • Implement sim-to-real transfer tooling: domain randomization configs, Cosmos Transfer integration, and quality validation ensuring synthetic data improves policy performance.
  • Build annotation platform backend systems — task taxonomy APIs, temporal segmentation, quality scoring, and inter-annotator agreement for robotics episode data.
  • Integrate with NVIDIA Isaac ecosystem (Isaac Sim, Isaac Lab, GR00T-Mimic, OSMO) to orchestrate synthetic data generation on cloud GPU infrastructure.

Required

  • MS or PhD in CS, Robotics, or ML (or equivalent industry experience). 2+ years shipping production systems — not just prototypes.
  • Strong Python and systems skills. Comfortable with Linux, Docker, CUDA, and cloud infrastructure (AWS/GCP).
  • Working knowledge of robot learning: imitation learning, behavior cloning, diffusion policies, or RL. You need to understand how VLA training works, not just the theory.
  • Experience with at least one robotics sim (Isaac Sim, MuJoCo, PyBullet, Gazebo) and robotics data formats/middleware (ROS/ROS2, URDF/USD, MCAP, HDF5).
  • Clean, tested, documented code. CI/CD and code review experience expected.

Preferred

  • Hands-on with VLA codebases: RT-2, Octo, OpenVLA, π0, GR00T N1, or LeRobot.
  • Experience with NVIDIA Omniverse, Replicator, or Cosmos for synthetic data; sim-to-real transfer techniques (domain randomization, NeRF, Gaussian Splatting).
  • Built ML eval frameworks, model benchmarking suites, or RLHF/DPO training pipelines.
  • Open-source contributions in robotics or ML. Published research in manipulation, embodied AI, or VLA systems is a plus.

Why This Role

  • Founding-stage impact. You're joining the robotics practice at inception. Your systems define how Deccan delivers physical AI data for years.
  • Frontier lab clients. Your work ships directly to teams like Google DeepMind. Few roles put you this close to the cutting edge of embodied AI.
  • Full-stack ownership. Annotation backends, VLA training integration, sim-based eval — you own entire systems, not isolated tickets.
From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against Deccan AI's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on Deccan AI's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    Deccan AI's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.