531 Deep Learning jobs in Noida
Deep Learning
Posted today
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Job Description
• Experience leading engineering teams from the first concept to ship
• Expert knowledge of deep learning techniques such as CNN, RNN, LSTM, and GAN
• World recognized expert knowledge and strong leadership experience in Deep Learning with an extensive publication record in peer-reviewed conferences and specialization in at least one of the following domains:
o Applications of deep learning techniques to traditional 3D computer vision topics such as Simultaneous Localization and Mapping (SLAM), Dense mapping, Eye tracking.
o Semantics and scene understanding.
o Scene segmentation.
o Object Detection and tracking.
o Hand tracking.
o Person tracking.
o Multi-task learning.
• Knowledge software optimization and embedded programming is a plus
Machine Learning/Deep Learning
Posted today
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Job Description
• Responsibilities Select appropriate datasets and data representation
• methods Data mining using state-of-the-art techniques
• Create and maintain optimal data pipeline architecture Assemble large, complex data sets
• That meet functional / non-functional business requirements
• Design and developing machine learning systems Implement appropriate ML algorithms to create and deploy AI models into production
Deep Learning Engineer (Freelancer)
Posted today
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Job Description
Key Deliverables:
- Design and train deep learning models for vision, NLP, and recommendations
- Optimize model performance for accuracy and efficiency
- Collaborate with engineering teams to deploy models into production
- Ensure scalability and robustness of AI pipelines
Role Responsibilities:
- Build state-of-the-art neural networks using DL frameworks
- Implement solutions with GPU acceleration for large datasets
- Maintain and tune models using experimentation and analytics
- Contribute to research and innovation within AI-driven systems
Skills Required
Deep Learning, Python, Tensorflow, Pytorch, Machine Learning
Senior Deep Learning Engineer
Posted 2 days ago
Job Viewed
Job Description
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.
Senior Deep Learning Engineer
Posted 2 days ago
Job Viewed
Job Description
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.
Senior Deep Learning Engineer
Posted 2 days ago
Job Viewed
Job Description
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.
Senior Deep Learning Engineer
Posted 2 days ago
Job Viewed
Job Description
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.
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Senior Deep Learning Engineer
Posted 2 days ago
Job Viewed
Job Description
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.
Senior AI Research Scientist - Deep Learning
Posted today
Job Viewed
Job Description
Key Responsibilities:
- Conduct cutting-edge research in deep learning and artificial intelligence.
- Develop, implement, and evaluate novel AI algorithms and models.
- Contribute to publications in leading AI conferences and journals.
- Collaborate with cross-functional teams to integrate AI solutions.
- Design and execute experiments to test and validate AI models.
- Stay current with the latest advancements in AI and machine learning.
- Mentor junior researchers and engineers.
- Develop and maintain robust AI research infrastructure.
- Translate research findings into practical applications.
- Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- 5+ years of research experience in deep learning.
- Strong publication record in top AI conferences (e.g., NeurIPS, ICML, CVPR, ACL).
- Expertise in deep learning frameworks (TensorFlow, PyTorch).
- Proficiency in Python and relevant libraries (NumPy, SciPy, Pandas).
- Experience in areas such as computer vision, NLP, or reinforcement learning.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and collaboration abilities.
- Proven ability to work independently and lead research projects in a remote setting.
Deep Learning Lead – AI-Driven Drug Discovery
Posted 4 days ago
Job Viewed
Job Description
We are seeking a Deep Learning Lead to architect, train, and deploy machine learning models for protein–ligand structure prediction, de novo molecular generation, and multi-objective optimization. You will partner closely with our Ligand Design & Pose Prediction Lead to integrate chemical and biological expertise into the model pipeline, ensuring our AI agents produce compounds that are potent, novel, and biologically relevant.
Key Responsibilities
Design and implement deep learning architectures for:
Pocket-conditioned molecular generation (e.g., Pocket2Mol, SE(3)-equivariant GNNs, 3D diffusion models).
Protein–ligand pose prediction (DiffDock, EquiBind, custom SE(3)-transformers).
Multi-objective reinforcement learning for compound optimization (potency, ADMET, novelty).
Fine-tune AlphaFold/OpenFold and related structure models for project-specific targets.
Integrate multi-modal biological context (from the Agentix Knowledge Graph) into generative and scoring models.
Develop and maintain scoring functions for binding affinity, selectivity, ADMET, and synthetic accessibility.
Implement uncertainty estimation and active learning loops to prioritize compound synthesis/testing.
Collaborate with the Ligand Design Lead to:
Translate medicinal chemistry insights into model constraints.
Incorporate wet-lab feedback into model retraining.
Co-develop workflows for real-time human–AI co-design.
Maintain MLOps pipelines for dataset versioning, model deployment, and experiment tracking.
Qualifications Required
PhD or MSc in Computer Science, Machine Learning, Computational Chemistry, Bioinformatics, or related discipline.
2+ years of hands-on experience in deep learning model development, ideally in a scientific or molecular domain.
Strong expertise in generative modeling (transformers, diffusion models, graph neural networks).
Experience with 3D geometric deep learning for molecular structures (SE(3)-equivariant architectures).
Proficiency in reinforcement learning (policy gradients, model-based RL, quality-diversity search).
Strong programming skills in Python with frameworks like PyTorch or TensorFlow.
Experience in handling molecular datasets (PDB, ChEMBL, binding affinity data).
Preferred
Prior work on protein structure prediction, ligand docking, or molecular property prediction.
Familiarity with cheminformatics toolkits (RDKit, Open Babel).
Experience in integrating wet-lab assay data into active learning loops.
MLOps experience (Docker, CI/CD for ML, MLflow, DVC).
Why Join Us?
You’ll help define the AI engine at the heart of Pattern’s platform, working with cutting-edge molecular AI tools and direct structural chemistry input from our Ligand Design Lead. Your models will power a proprietary agentic search system designed to explore the chemical universe faster and smarter than competitors.