Deep Learning Engineer
carbonrobotics
Deep Learning Engineer
nanonets· Deep Learning
About this role
About Us:
Nanonets agents are built for complex business processes. Ranked #1 in understanding unstructured data and applying business rules in processes like accounts payable, order management, and supply chain.
Nanonets agents handle the exceptions other tools miss, reducing processing time by 94% and delivering clean data to SAP, Salesforce, or any system of record. That's why global enterprises reach for Nanonets when workflows are complex and accuracy is non-negotiable.
Learn more about us here:
About the Role
The role can be summed up as building and deploying cutting edge generalised deep learning architectures that can solve complex business problems like converting unstructured data into structured format without hand-tuning features/models. You are expected to build state of the art models that are best in the world for solving these problems, continuously experimenting and incorporating new advancements in the field into these architectures.
What we’re looking for
- 5-8 years of experience in Deep Learning.
- Strong foundational knowledge in deep learning concepts and architectures (LLMs and VLMs)
- Demonstrated expertise in at least one specialised area of deep learning (NLP, computer vision, multimodal models, etc.)
- Experience building and deploying production-grade Deep Learning systems at scale,
- Familiarity with various large language models (GPT, LLaMA, Claude, etc.) and their applications
- Strong software engineering practices including version control, CI/CD, and code quality
- Ability to rapidly learn and apply new technologies and approaches.
Interesting Projects Other Senior DL Engineers Have Completed
- Deployed large scale multi-modal architectures that can understand both text and images really well.
- Built an auto-ML platform that can automatically select the best architecture, fine-tuning method based on type and amount of data.
- Best in the world models to process documents like invoices, receipts, passports, driving licenses, etc.
- Hierarchical information extraction from documents. Robust modeling for the tree-like structure of sections inside sections in documents.
- Extracting complex tables — wrapped around tables, multiple fields in a single column, cells spanning multiple columns, tables in warped images, etc.
- Enabling few-shots learning by SOTA finetuning techniques.
Frequently Asked Questions
Is the salary disclosed for the Deep Learning Engineer position at nanonets?
The salary for this Deep Learning Engineer role at nanonets is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Deep Learning Engineer position at nanonets located?
This Deep Learning Engineer role at nanonets is based in Bengaluru, Karnataka, India. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Which team or department does the Deep Learning Engineer at nanonets belong to?
This Deep Learning Engineer position is part of the Deep Learning department at nanonets. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Deep Learning Engineer position at nanonets?
Click the "Apply Now" button on this page. You will be redirected to nanonets's official application portal hosted on greenhouse where you can submit your application directly.
When was the Deep Learning Engineer job at nanonets posted?
This Deep Learning Engineer position at nanonets was posted on Jul 28, 2026. Apply as soon as possible — early applications are often reviewed first.
Deep Learning Engineer
nanonets
You'll be redirected to nanonets's official application page on Greenhouse.