145 Deep Learning jobs in India

About Nanonets

Nanonets is redefining how companies automate document-heavy and unstructured data workflows using AI Agents. Our customers include global leaders like Adobe, Schneider Electric, and Boston Scientific. We're backed by marquee investors and are growing fast. We're looking for exceptional engineers to join our mission-driven team.

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.

About Nanonets

Nanonets is redefining how companies automate document-heavy and unstructured data workflows using AI Agents. Our customers include global leaders like Adobe, Schneider Electric, and Boston Scientific. We're backed by marquee investors and are growing fast. We're looking for exceptional engineers to join our mission-driven team.

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.

Job Role  - Deep Learning Consultant

Experience  - 2+ Years

Location  - Bangalore (Hybrid)

Tech Stacks   - SQL, AWS Redshift, Python,  ML,  Deep Learning (Pytorch/Tensorflow)

Job Description:

We are seeking a highly skilled and motivated Deep Learning Consultant to join our team. This role requires hands-on experience in building and deploying deep learning models, proficiency in core Machine Learning (ML) principles, and advanced projects. The ideal candidate should also be experienced in using AWS cloud services for machine learning workflows and possess 2-3 years of industry experience working on real-world deep learning problems.

Key Responsibilities:

• Design, develop, and implement deep learning models for various business applications, leveraging state-of-the-art techniques in computer vision, natural language processing, or other domains.

• Apply core machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch) to solve complex business problems.

• Lead advanced machine learning projects, collaborating with cross-functional teams, from data preprocessing to model deployment.

• Evaluate model performance and improve model accuracy through hyperparameter tuning, feature engineering, and other optimization techniques.

• Deploy, scale, and manage machine learning models on AWS cloud services such as Amazon SageMaker, EC2, Lambda, and S3.

• Collaborate with data engineers and data scientists to ensure smooth integration of ML models into production systems.

• Stay up to date with the latest research and trends in deep learning and machine learning, applying cutting-edge techniques to business challenges.

• Provide technical mentorship and guidance to junior team members in deep learning and ML best practices.

Required Qualifications:

• 2-3 years of hands-on experience in developing and deploying deep learning models.

• Strong experience in core ML algorithms and frameworks such as TensorFlow, PyTorch, Keras, etc.

• Proven track record of delivering advanced machine learning projects from concept to deployment.

• Experience in using AWS cloud services for machine learning workflows (e.g., Amazon SageMaker, EC2, Lambda, S3, etc.).

• Experience in data preprocessing, feature engineering, and model optimization.

• Strong programming skills in Python (or other relevant languages) and experience with libraries like NumPy, pandas, etc.

• Excellent problem-solving skills with a keen attention to detail.

• Ability to work independently and in a collaborative environment with cross-functional teams.

Preferred Qualifications:

• Experience in handling large-scale datasets and model training on distributed systems.

• Familiarity with ML Ops and deploying models in a production environment.

• AWS Certification in Machine Learning or Data Science.

• Knowledge of DevOps practices for ML, such as continuous integration/continuous delivery (CI/CD) pipelines.

NVIDIA is known as “the AI computing company.” Come, join our Deep Learning team, where you can help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field. We are currently seeking an experienced senior software engineer with strong Deep Learning and System Programming fundamentals coupled with robust C/C++ skills to contribute to the development of NVIDIA Maxine Audio - a comprehensive suite of SDKs, Microservices and APIs that enable AI-driven features for video conferencing, content creation and gaming.

What you’ll be doing:

• Architect and lead development of next-generation Deep Learning and multimedia algorithms for processing of speech and audio applications.

• Train Speech Enhancement models, assess them for quality, performance, and finetune them.

• Analyze model accuracy and bias and recommend the next course of action & Improvements.

• Improve processes for speech data processing, augmentation, filtering & training sets preparation.

• Optimize algorithms for optimal performance on the GPU tensor cores

• Collaborate with various teams to drive an end to end workflow from data curation and training to performance optimization and deployment

• Influence strategic decisions in the team and product roadmap

• Partner with system software engineers and validation teams to build and ship production-quality code.

What we need to see:

• PH.D./MS in Computer Science or a closely related engineering field with 3+ years of relevant experience

• Strong background in Deep Learning including model design, pruning & performance optimization, transfer learning etc

• 4+ years of experience of leading cross-module projects and taking them to productization

• Strong software engineering background with proficiency in C or C++

• Hands-on expertise with PyTorch, TensorRT, CuDNN and one or more Deep Learning frameworks (Tensorflow, Keras etc)

• Familiarity/expertize with various cloud frameworks e.g. AWS, GCP, Azure is a big plus

• CUDA programming experience is a plus

• Excellent communication and collaboration skills

• Self-motivated and able to find creative practical solutions to problems

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.