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
Somewhere between the pleasing loss curve of a generative AI model for robot control and the reality of a pipette tip actually picking up liquid, there is a person with a screwdriver, a soldering iron, and a Python script held together with sheer willpower.
That person is you.
PopVax is building something unusual: a wet lab where low-cost general-purpose robotic arms, guided by learned control models, autonomously execute complex scientific experiments alongside more traditional lab automation equipment. We have machine learning engineers building the brains. Now we need someone to build the body — and more importantly, to make the brains and the body actually talk to each other.
This is the role for the engineer who lives in the seam between hardware and software. The one who can wire up a motor controller in the morning, calibrate an end-effector over lunch, write a ROS node in the afternoon, and debug a serial communication issue with an OpenTrons liquid handler before going home.
What You'll Actually Do
You'll be responsible for getting our robots physically set up, calibrated, integrated, and running end-to-end in a real wet lab environment. This means robotic arms — selecting, mounting, wiring, calibrating, and maintaining them — but it also means working with more traditional lab automation equipment like OpenTrons liquid handlers, plate readers, and other instruments that need to be incorporated into automated workflows.
The key word in this role is "glue." You are the person who glues systems together. Sometimes that glue is software — a driver, an API wrapper, a control script, a state machine that coordinates multiple pieces of hardware. Sometimes that glue is physical — a custom bracket, a rewired connector, a sensor mount that doesn't exist yet so you design and build it yourself. Sometimes that glue is a conversation — sitting down with the machine learning team and figuring out exactly what coordinate frame the model expects, or sitting down with a wet lab scientist and understanding why the robot's gripper keeps knocking over the tube rack.
You will not have the luxury of working on one system in isolation. The whole point is integration — making heterogeneous hardware, software, and scientific workflows operate as a coherent system that scientists can actually rely on.
Specifically, you will:
Set up and calibrate robotic arms end-to-end. From unboxing to first successful pipetting action. Mechanical mounting, electrical wiring, sensor integration, kinematic calibration, end-effector design and attachment, workspace setup — you own the entire physical stack. When the arm drifts by two millimetres and misses the well, you figure out whether it's a calibration issue, a thermal expansion issue, a mounting issue, or a software issue, and you fix it.
Integrate traditional lab automation equipment. OpenTrons liquid handlers, plate readers, incubators, centrifuges, and whatever else the scientists need incorporated into automated workflows. These instruments often have their own APIs, protocols, and quirks. You'll write the software interfaces, build the physical integrations, and make them play nicely with the rest of the automation stack.
Collaborate closely with the machine learning team. The learned control models need to operate on real hardware, with real sensors, in real time. You'll be the person who ensures the hardware is set up in a way that the models can actually use — the right cameras in the right positions, the right calibration, the right action spaces, the right data streaming pipeline. When the model says "move to position X" and the arm goes somewhere else, you'll debug it together with the ML engineers — and it'll usually be a bit of both your problems.
Design and build custom hardware solutions. Off-the-shelf doesn't always cut it in a wet lab automation setting. You'll design and fabricate custom mounts, fixtures, adapters, and end-effectors. You'll work with 3D printers, basic machining tools, soldering stations, and whatever else is needed to make the physical setup work. If a bracket doesn't exist, you make it. If a connector doesn't fit, you modify it. If a sensor needs to go somewhere the manufacturer never intended, you figure it out.
Write the software that ties it all together. Drivers, control interfaces, communication protocols, state machines, monitoring scripts, safety interlocks — the software layer that sits between the high-level intelligence and the physical hardware. This isn't the machine learning layer and it isn't a web app — it's the real-time, close-to-the-metal software that makes a robotic system actually function reliably. Python, C/C++, ROS, serial protocols, whatever the system needs.
Keep things running. Robots in labs break. Cables wear out. Calibrations drift. Sensors get splashed with buffer. You'll maintain the hardware, troubleshoot failures, and build the monitoring and diagnostic systems that let you catch problems before they ruin an experiment. Uptime matters — when a robot goes down, an experiment doesn't happen.
Who You Are
You're a mechatronics engineer at heart — someone who genuinely enjoys the intersection of mechanical systems, electronics, and software, and who gets uncomfortable when asked to work on only one of the three. You've built physical systems that actually work, not just simulated ones. You've soldered boards, machined parts, written firmware, debugged signal integrity issues, and gotten a robot to do something useful in the real world.
You're a systems integrator by instinct. When you see three pieces of equipment that don't talk to each other, your brain immediately starts figuring out how to make them talk to each other. You're not precious about how — if the right solution is an elegant API integration, great; if the right solution is a jury-rigged serial cable and a Python script running on a Raspberry Pi, also great. You care about whether it works, not whether it's pretty.
You're comfortable in a lab. You understand that a wet lab is not a machine shop — there are liquids, biological materials, and expensive reagents everywhere, and the robots you build need to operate reliably in that environment without contaminating anything or being contaminated. You don't need a biology background, but you should be willing to learn enough about what the scientists are doing to understand why your calibration being off by a millimetre actually matters.
Qualifications
B.Tech, M.Tech, or equivalent in Mechatronics, Electrical Engineering, Robotics, Mechanical Engineering, or a related field.
Strong hands-on experience with robotic systems — arm setup, calibration, sensor integration, end-effector design.
Solid electronics skills — circuit design, soldering, wiring, sensor interfacing, motor controllers, basic PCB work.
Software proficiency in Python and C/C++. Experience with ROS or similar robotics middleware is a strong plus.
Experience with CAD tools and rapid prototyping (3D printing, basic fabrication).
1–4 years of experience. Strong fresh graduates with serious project or competition experience in robotics are very welcome.
Preferred (but not required)
Experience with lab automation equipment (OpenTrons, Hamilton, Beckman, Tecan, or similar).
Familiarity with computer vision systems, camera calibration, and sensor fusion.
Experience with real-time control systems or embedded programming.
Exposure to biology labs, scientific instrumentation, or research environments.
Reporting Structure
You'll report to Darshit Mehta, VP of Programs, who worked on automating high-throughput wet lab experimentation at Ginkgo Bioworks — one of the pioneers of the self-driving lab concept — and who has strong opinions, learned the hard way, about what actually works when you put robots in biology labs. You'll work hand-in-glove with PopVax's machine learning team, building the physical platform that their models operate on. And you'll collaborate daily with Soham Sankaran, Founder & CEO, who was a robotics PhD student at Cornell and started a Y Combinator-backed robotics company before founding PopVax — and who will almost certainly show up at your workstation unannounced to ask why the arm is making that noise.
You'll also work closely with PopVax's wet lab scientists, who are the ultimate judges of whether the automation works. If the robot can't reliably execute their protocols, nothing else matters.
This is a role for someone who loves making physical systems work — really work, not just demo-work — and who wants to do it in a place where the systems you build will directly accelerate the development of vaccines and immunotherapies. If you're happiest when you've got a screwdriver in one hand, a terminal open on your laptop, and a problem that spans hardware, electronics, and software all at once, this is your job.