nanonets company
Nanonets is transforming the way businesses work. Our AI platform takes the manual, messy, time consuming work — that bog down industries like finance, healthcare, supply chain, and more — and turns them into seamless, automated processes. What once took hours of human effort now takes seconds with Nanonets. Our client footprint spans across 34% of Fortune 500 enabling businesses across various industries to unlock the potential of AI in automating their business processes.
More than 10,000 businesses trust Nanonets because we don’t just promise efficiency — we deliver it with unmatched accuracy, seamless integrations.
In 2024, we raised a $29M Series B led by Accel with continued backing from Elevation Capital and YCombinator, fueling our mission to reshape entire industries through intelligent automation. With revenues tripling year over year and a rapidly scaling global team, we’re not just imagining the future of work — we’re building it.
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The Role
We’re looking for a Deep Learning Analyst to help our customers unlock maximum value from the Nanonets Deep Learning Platform.
This role sits at the intersection of technical problem-solving, customer success, and product improvement — ensuring every customer achieves successful implementation and high model accuracy.
Single KPI:
👉 Number of successful customer implementations leveraging Nanonets’ Deep Learning Platform.
What You’ll Do
What We’re Looking For
We’re seeking someone who is a strong problem solver, customer-focused, and takes ownership end to end.
Ideal candidate profile:
Note: Prior AI/ML experience is not required — strong fundamentals and problem-solving skills are sufficient.
Role Details
This is a fully remote role (anywhere in India) on a third-party contract for 1 year, with the option to extend. You’ll work in IST hours and be on third-party payroll — giving you flexibility and autonomy.
Interesting Projects Other DL Engineers Have Completed
VLM + LLM Innovation: From text to vision-language, we are solving alignment, hallucination reduction, and cross-modal understanding at scale - leveraging the latest techniques like RLHF, PEFT, and advanced fine-tuning to push what’s possible.