PopVax is an Indian full-stack biotech building first-in-class and best-in-class vaccines and cancer immunotherapies using machine learning-driven protein design and relentless empiricism. We design, develop, and manufacture our own RNA medicines end-to-end because we believe great pharmaceutical science can only flourish in tight feedback loops that iterate rapidly. PopVax’s experimental work and clinical dose production is based at the RNA Foundry, our integrated R&D and GMP-capable clinical dose production facility in Hyderabad.

PopVax's north star is our goal of developing novel vaccines and therapeutics over the next decade with the cumulative ability to save 1 million lives each year – the Million Lives Mission. To that end, we are developing first-in-class vaccines against Hepatitis C, Strep A, and adult pulmonary TB; broadly-protective best-in-class vaccines against COVID-19, influenza, malaria, and HPV; and precision immunotherapies against hard-to-treat solid tumours such as liver cancer and pancreatic cancer. Beyond existing diseases, we are leveraging our high-speed platform to build rapid-response biosecurity capabilities against engineered de novo pathogens.

Our mission is funded by Vitalik Buterin’s Balvi Fund, the Gates Foundation, the US Biomedical Advanced Research and Development Authority (BARDA), Renaissance Philanthropy, and Good Ventures, with individual investments from Enveda founder Viswa Colluru and Tesla self-driving AI pioneer Dhaval Shroff. Our first program, an open-source broadly-protective COVID-19 vaccine, will begin a Phase I clinical trial in Australia in mid-2026. This is just the start – we intend to advance 6+ novel vaccine and immunotherapy programs into human clinical trials over the next three years, decisively demonstrating that world-class biotech R&D is possible in India. 

No matter the job title, each person’s role at PopVax is ultimately about helping bring safe, effective new medicines that represent a step-change over the current standard-of-care to the people who need them, as quickly as possible. If you are looking for a place where the ambition is high, the learning curve is steep, and the work matters to billions, you’ll feel at home here.

If you’re excited by the idea of advancing scientific, clinical, and regulatory frontiers of vaccines and immunotherapies, spending each day developing medicines with the potential to save millions of lives, and building a generational global pharmaceutical company in India along the way – join us!

Role Overview

Most software engineers build products for users they've never met. You won't have that problem. Your users will be ten feet away from you, pipetting something into a 96-well plate.

PopVax is a full-stack mRNA biotech company — we design, develop, and manufacture vaccines and immunotherapies, and we take them to clinic at a pace that makes most pharma companies nervous. Our labs are where the core work happens: experiments are designed, samples are processed, assays are run, data is generated, and decisions are made that determine whether a vaccine candidate moves forward or doesn't.

Here's the thing about labs, though — even very good ones. The science is cutting-edge, but the software that supports it often isn't. A scientist finishes a run on an instrument and spends the next three hours copy-pasting outputs into a spreadsheet to make a graph. An experiment's results live in one person's notebook and another person's email and a third person's USB drive. A project manager asks "where are we on this program?" and the answer requires assembling information from six different places, none of which talk to each other.

These aren't science problems. They're software problems. And they slow down the science.

We need someone who will sit inside the lab, understand the science well enough to ask the right questions, and build the software that makes the whole operation faster, smarter, and less dependent on manual drudgery.

That someone is our Benchside Software Engineer.

What You'll Actually Do

You'll be embedded — physically — in the lab. Not supporting it from a desk three floors away, not building tools based on a requirements doc someone emailed you. You'll attend team meetings, watch how experiments are run, see where data gets stuck, notice where a scientist is doing something by hand that a script could do in seconds, and then go build the thing that fixes it.

The "product" in this role is whatever makes the scientists faster and smarter. Some weeks that'll be a data pipeline. Other weeks it'll be a dashboard. Other weeks it'll be a small internal tool that automates something nobody even realized could be automated until you pointed it out.

Specifically, you will:

• Build workflow software. Design and build internal tools and lightweight applications that digitise, track, and accelerate experimental workflows — from experiment design through data capture to results. Right now, some of these workflows involve whiteboards, spreadsheets, and verbal handoffs. You'll turn them into something that actually scales.

• Create data pipelines that work. Experiments and instruments generate raw data. That data needs to become clean, structured, and usable — by scientists who want to interpret results, by leadership who want to track program progress, and by teams who need to make decisions quickly. You'll build the pipelines that make raw outputs into something people can actually act on.

• Build dashboards that tell the truth. R&D teams and leadership need real-time visibility into experimental progress, assay results, and program status. You'll build internal dashboards that surface this information clearly — not vanity metrics, but the views that help people understand where things stand and what needs attention.

• Replace manual coordination with software. Lab operations involve a surprising amount of repetitive coordination work — tracking samples, scheduling instrument time, managing inventory, communicating status across teams. You'll identify the places where people are doing this by hand and build software that just handles it.

• Understand before you build. This is perhaps the most important part. You'll spend real time with scientists. You'll learn what experiments they're running, how data flows from bench to decision, and where things break down. You'll ask questions — lots of them — and build tools that fit how people actually work, not how you imagine they work from the other side of a Jira ticket.

Who You Are

You're a software engineer who is genuinely curious about science. You don't need a biology degree — we'll teach you the biology. But you should be the kind of person who, when a scientist explains what an mRNA lipid nanoparticle does, leans in rather than glazes over. The curiosity matters because you can't build good tools for a domain you don't care about understanding.

You're a strong generalist. Python is probably your primary tool, but you pick up whatever's needed — a new framework, a dashboarding library, a database you haven't used before. You've built things end-to-end: a data pipeline, an internal tool, an analysis dashboard, a script that saved someone hours of tedious work. It doesn't have to be fancy. It has to be real, and you have to be able to show us.

You ask good questions. You spend time understanding the problem before jumping to the solution. You've probably been the person in a group project who said "wait, what are we actually trying to do here?" and saved everyone a week of wasted work.

Qualifications

• B.Tech, M.Tech, or M.Sc in Computer Science, Engineering, or a related field.

• 0–3 years of experience. Strong fresh graduates with the right project instincts are very welcome.

• Solid programming ability in Python and a willingness to learn whatever else the problem requires.

• A portfolio of something you've built end-to-end — a pipeline, a tool, a dashboard, a useful script. Show us you can go from problem to working solution.

• Genuine curiosity about science and a willingness to spend time in a lab learning how things work.

Preferred (but not required)

• Experience building internal tools, data pipelines, or analytics software in any domain.

• Familiarity with scientific or research data — even from a university lab project counts.

• Experience with dashboarding tools, databases, or API integrations.

Reporting Structure

You'll report to the VP of Programs, Darshit Mehta, who worked on exactly these kinds of problems — building software infrastructure for lab operations — at Ginkgo Bioworks, one of the world's leading synthetic biology companies. He knows what good looks like here, and he'll help you get there. You'll also work side-by-side with R&D, GMP, and QA teams daily, and PopVax's Founder & CEO, Soham Sankaran — a lapsed computer scientist who still can't resist a good systems problem — will work closely with you as well. This is not a role where you get requirements in a ticket and deliver code in a pull request. You'll be in the room where the science happens, and the software you build will directly shape how well and how fast that science gets done, which decides whether and how quickly we’re able to get our vaccines and immunotherapies into clinic to save lives.