Developer Advocate — AI & GPU Workflows

Full-time · Bengaluru · Hybrid

JarvisLabs needs a builder who can make real AI workflows work and help other developers reproduce them. You’ll use our GPU compute and model deployment tools, build examples, explain the trade-offs and learn from the people trying them.

You will work across engineering, teaching and developer marketing, closely with the founder and technical team. The responsibility includes code, documentation, distribution, troubleshooting and useful product feedback.

Product Focus

An early priority is helping developers build with models as an API: calling models from their applications without managing the underlying GPU infrastructure. You’ll use the APIs yourself and build tested examples that take a developer from setup and a first successful API call to a useful application. Explain costs, limitations and failure cases from what you actually run and verify.

Your work also spans GPU containers and VMs, and model deployment products. Help developers understand when an API fits their needs and when their workload needs direct access to GPU compute or a custom deployment.

What You Will Own

• Build and publish runnable model API integrations, with setup instructions, error handling and clear explanations of usage and costs.
• Build practical examples around workloads such as model inference, fine-tuning, image or video generation, and applications that use model APIs.
• Turn those examples into clear tutorials, repositories, documentation improvements, live demos and short walkthroughs.
• Explain setup, costs, trade-offs and failure cases. Validate technical and performance claims before publishing them.
• Share your work in relevant developer communities, answer questions and run sessions where people can try the workflow themselves.
• Bring recurring questions and setup problems back to engineering and help improve the developer experience.
• Work with growth colleagues to learn which examples bring relevant users to JarvisLabs and help them succeed.

What We Are Looking For

• Evidence of building and teaching: a repository, tutorial, article, demo, workshop or open-source contribution you can explain in depth.
• Ability to write and debug Python, use APIs and command-line tools, and understand the code you publish.
• Clear technical communication, including prerequisites, trade-offs and failure cases.
• Initiative when something breaks: form a hypothesis, investigate, solve what you can and give engineering useful evidence.
• Care for reproducibility, documentation and the experience of someone following your instructions.
• Hands-on experience using AI tools to build, debug and explain working software. You can show what you shipped, explain the code, and describe how you reviewed and tested the result.

Strong Pluses

• Experience in developer advocacy, ML engineering, technical writing or education.
• Familiarity with PyTorch, Hugging Face, Docker, vLLM, ComfyUI or related tools.
• Work with model deployment, GPU workloads, benchmarks or production AI applications.
• An independent project, open-source contribution or community where you helped others build successfully.

You can learn parts of the stack on the job. Relevant work matters more than a particular title or employer.

How We Work

You’ll take examples through implementation, explanation, distribution and follow-up. Documentation and troubleshooting are part of delivery. You’ll use AI tools to build and ship with the resources available, without first needing to hire a team or outsource execution. You own the finished output—its accuracy, usefulness and quality. Untested code and generic AI-generated tutorials that you haven’t worked through yourself do not meet the bar. We expect you to check technical claims, make limitations clear and use developer questions to improve the product.

Early progress means tested model API examples, developers making their first successful calls and building useful applications, and feedback that improves both the examples and their experience on JarvisLabs.

What To Send

Email [email protected] with the subject Developer Advocate — AI & GPU Workflows.

Include:

• Why JarvisLabs, and which technical problem or developer audience interests you.
• A few sentences on what you could contribute in your first 90 days.
• Two or three links to code, tutorials, demos, talks or other relevant work.
• Your contribution to one example, who it helped and a problem you debugged.
• One example of work delivered using AI tools: what the tools did, what you changed or rejected, and how you verified the final result. This can be one of the examples above.
• Your location and availability. Add a CV or LinkedIn profile if useful.

We review a personal note and evidence of work; CV-only applications are not reviewed. Existing public work or a shareable anonymised sample is enough to start. If there is a better way to show your work, use it.