How to Get Hired at sarvam

Sarvam is one of India's most exciting AI startups, building large language models, voice AI, and speech technology designed specifically for Indian languages. If you have ever wanted to work on AI that actually understands Hindi, Tamil, Telugu, Bengali, or Kannada natively, rather than just translating from English, Sarvam is one of very few places in India doing this at a serious scale.

The company was founded with a clear mission: make AI useful for every Indian, not just English speakers. That mission has attracted researchers, engineers, and builders who want their work to have direct impact on hundreds of millions of people.

As of early July 2026, Sarvam has 68 open roles across engineering, research, product, design, and operations. The openings span a wide range including ML research scientists, backend engineers, front-end developers, DevOps, and go-to-market roles. Because Sarvam is a growth-stage startup, the team moves fast and new roles open up regularly.

Sarvam's hiring process typically moves through four to five stages, though the exact structure can vary depending on the role and team.

Stage 1: Application and resume screening. Your resume goes through an initial filter by the recruiting team. They look for relevant experience in ML, software engineering, or whatever domain the role requires. A strong GitHub profile, research publications, or open source contributions can help your application stand out at this stage.

Stage 2: Recruiter or HR call. If your profile matches, you will usually get a short call with someone from the people team. This is a conversation about your background, why you are interested in Sarvam, and logistics like notice period and location preference.

Stage 3: Technical assessment. For engineering and research roles, expect a take-home assignment or a live coding round. ML roles may ask you to solve a problem involving NLP, speech processing, or model fine-tuning. Software engineering roles typically test your data structures, algorithms, and system design thinking.

Stage 4: Technical interviews. This is usually one or two rounds with senior engineers or researchers on the team. Expect deep questions on your past projects, your understanding of language models, and how you approach ambiguous problems. For research roles, you may be asked to discuss a paper you have worked on or found interesting.

Stage 5: Founder or leadership round. For senior or specialist roles, there is often a final conversation with a founder or senior leader. This round is less about grilling you on code and more about understanding how you think, what you care about, and whether you are a fit for a fast-moving, mission-driven environment.

The full process from application to offer can take a few weeks, though startups can move faster when they find someone they really want.

Sarvam is not a company where you coast on a brand name or check boxes. They want people who are genuinely excited about the problem space.

For technical roles: Strong fundamentals in Python and ML frameworks like PyTorch are expected. If you are applying for NLP or speech roles, knowing your way around transformer architectures, fine-tuning workflows, and evaluation metrics matters a lot. They value people who have actually built and shipped something, not just those who have read about it.

For research roles: A track record of independent thinking, prior publications or preprints, and comfort with uncertainty are all signals they watch for. You do not need to have worked at a big lab, but you should have a clear point of view on the problems you have worked on.

For non-technical roles: Product managers, growth, and operations folks need to be comfortable in a startup context where things change quickly. Prior experience in a B2B SaaS or developer-facing product company is a plus.

Across all roles: Sarvam wants people who care about building for India, not just building in India. If your motivation is purely the resume line, it will show in the interview.

Know the product. Before any interview, spend real time with Sarvam's publicly available tools and demos. Understand what Sarvam-1 does, how their text-to-speech and speech recognition models compare to alternatives, and what problems they are solving for Indian language users. Interviewers notice when candidates have actually used the product.

Read their research. Sarvam publishes papers and technical blogs. Going through their published work and being able to discuss the choices they made will set you apart from candidates who only skimmed the website.

Brush up on Indian language NLP. If you are applying for a technical role, understanding the specific challenges of low-resource languages, transliteration, and code-switching (mixing English and a regional language mid-sentence) will help you speak the interviewer's language.

Prepare your story. Have a clear two-minute version of who you are, what you have built, and why Sarvam specifically. Generic answers about 'wanting to work in AI' will not land well here. Connect your background directly to their mission.

Practice system design with Indian scale in mind. For engineering roles, think through how you would design a speech recognition pipeline that handles multiple Indian languages, or a serving infrastructure that needs to run inference cheaply across millions of users.

Sarvam operates with the energy of a company that believes it is building something that genuinely matters. The team skews young, research-forward, and mission-driven. Decisions move fast, roles can stretch well beyond their job description, and you are expected to take ownership without waiting for someone to tell you what to do next.

The culture values intellectual honesty. If something is not working, people are expected to say so clearly rather than paper over it. This can be refreshing if you are coming from a large company where politics slow things down, but it can be an adjustment if you are used to more structured environments.

Work can be intense, especially around product launches or model releases. The team generally believes this is worth it given what they are building, but going in with eyes open about startup pace is important.

Sarvam cares about India as a market and as a mission. People who thrive here tend to have a personal connection to the problem: growing up speaking a regional language, having family members who struggle with English-first technology, or simply believing that most of the world's AI tools are built for a narrow slice of the global population.

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