Deep Learning Analyst - Customer Success and Product Improvement

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.

Read about the release here:

Article 1

Article 2

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

• Engage with customers to deeply understand their use cases, data, and automation goals.
• Analyze model performance and identify improvement opportunities to enhance accuracy.
• Work iteratively to optimize models and help customers achieve higher levels of automation.
• Collaborate closely with the Product and Engineering teams to drive platform-level solutions.
• Translate customer feedback into actionable insights and technical enhancements.
• Ensure smooth, successful deployment and measurable business impact for every customer.

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:

• 2–4 years of experience as a Software Engineer, Data Engineer, Deep Learning Engineer or Data Scientist
• Hands-on Python experience is a MUST have
• Experience with LLMs and GenAI is preferred
• SQL is a definitive plus
• Strong analytical and troubleshooting skills
• Curiosity, motivation, and a “figure-it-out” mindset
• A B.Tech degree or equivalent technical background

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

• Setting New Standards: Through our Automation Benchmark, we are defining how AI systems are measured on grounding, reliability, and performance.
• Proven Adoption: Our Nanonets-OCR-S model on Hugging Face has already ~225,000 downloads, validating its global impact and utility.
• Global Recognition: Our research and open-source contributions are recognized by leading voices in AI (example).
• Enterprise-Ready AI: Our models don’t just output predictions - they provide grounded answers with confidence scores to enable trustworthy decision-making.
• Agentic OCR Systems: Unlike traditional OCR, our models are agentic - capable of reasoning about inputs, adapting to task context, and chaining multiple steps to deliver structured, actionable data.

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.