376 AI Researcher jobs in India

The position entails designing and developing cutting-edge deep learning models for computer vision applications.

• Design, Develop, Deploy : Design, develop, and deploy deep learning models for image classification, object detection, segmentation, pose estimation, OCR, and related tasks.
• Data Management : Work with large-scale datasets (images, videos, annotations), including data cleaning, augmentation, and preprocessing pipelines.
• Evaluation and Fine-Tuning : Evaluate and fine-tune models using metrics like IoU, mAP, F1 score, and accuracy.
• Research and Experimentation : Conduct research and experimentation with state-of-the-art architectures such as CNNs, Transformers (ViT, DETR), GANs, and self-supervised learning.
• Cross-Functional Collaboration : Collaborate with cross-functional teams to integrate models into production pipelines (cloud/on-prem).
• Staying Current : Stay current with the latest advancements in computer vision and contribute to the company's innovation roadmap.
• Model Explainability : Develop tools for model explainability and performance monitoring in production environments.

• Educational Background : B.Tech, Master's or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, or a related field.
• Experience : 3+ years of experience in developing and deploying deep learning models for computer vision tasks.
• Technical Skills : Strong proficiency in Python and deep learning frameworks like PyTorch and TensorFlow.
• Hands-on Experience : Hands-on experience with libraries such as OpenCV, Albumentations, MMDetection, Detectron2, or YOLOv5/8.
• Distributed Training : Experience training and optimizing models on GPU clusters using distributed training (e.g., PyTorch Lightning, DDP).
• Model Deployment : Familiarity with model deployment (ONNX, TensorRT, TorchScript) and serving (FastAPI, Flask, Triton Inference Server).
• Annotation Tools : Experience with annotation tools (e.g., CVAT, Labelbox) and data versioning tools (e.g., DVC, Weights & Biases).
• Computer Vision Metrics : Strong understanding of computer vision metrics and evaluation protocols.
• Mathematical Algorithmics : Strong skillset in mathematical algorithmics and explainability of deep learning models and frameworks.

• 3D Vision : Knowledge of 3D vision, SLAM, multi-view geometry and YOLO.
• Video Datasets : Experience working with video datasets and spatio-temporal models.
• Semi-Supervised Learning : Background in self-supervised or semi-supervised learning.
• MLOps Pipelines : Familiarity with MLOps pipelines and tools like MLflow, Kubeflow, or SageMaker
• Domain-Specific Application : Experience in a domain-specific application like medical imaging, aerial imagery, or autonomous vehicles.

• Impactful AI Products : Work on impactful AI products at the cutting edge of computer vision.
• Cross-Functional Team : Collaborate with a world-class team of researchers and engineers.
• State-of-the-Art Infrastructure : Access to state-of-the-art GPU infrastructure and training platforms.
• Flexible Work Environment : Flexible work environment with competitive compensation and benefits.

About the Role

QpiAI works at the intersection of AI and Quantum Computing, developing groundbreaking solutions to tackle some of the most complex challenges across various industries. Our team is dedicated to pushing the boundaries of innovation and delivering exceptional results to our enterprise clients, driving significant impact.

We are seeking an exceptional Applied AI Researcher to join our innovative research team. This role will focus on advancing our AI capabilities through rigorous experimentation, multi-agent systems design, domain-specific scaffolding, and evaluation methodology development. Through this role you will get the opportunity to develop Compound AI systems impacting areas like Drug Discovery, Decision Intelligence, Chip Design , Quantum Computing etc.

Key Responsibilities

• Design and implement novel multi-agent architectures that enable complex problem-solving and collaboration
• Develop domain-specific scaffolding techniques to guide AI systems in specialized environments
• Create and curate high-quality datasets for training and evaluating AI systems across various domains
• Establish comprehensive evaluation frameworks to measure system performance, robustness, and alignment
• Research and implement reinforcement learning approaches for agent behavior optimization
• Develop techniques for post-training optimization and domain adaptation
• Collaborate with cross-functional teams to translate research findings into practical applications
• Stay current with the latest advancements in AI research and contribute to the research community
• Document methodologies, findings, and best practices for internal knowledge sharing

Qualifications

• Advanced degree (MS or PhD) in Computer Science, Machine Learning, AI, or related technical field
• 4+ years of experience in applied AI research
• Strong mathematical foundations in optimization, probability theory, and linear algebra
• Extensive expertise in Python programming and software development
• Strong proficiency in PyTorch or JAX for implementing and scaling AI models
• Experience in curating datasets, pre-training, and aligning multimodal small language models
• Demonstrated experience with various reinforcement learning post-training methods (RLHF, DPO, GRPO, SFT, etc.)
• Experience with prompting methods like Chain of Thought and curating Chain of Thought datasets
• Experience training small reasoning models for specific applications
• Familiarity with various alignment methods and value learning techniques
• Experience with multi-agent systems design and implementation
• Knowledge of distributed training on multi-node, multi-GPU clusters
• Experience with dataset curation, cleaning, and augmentation for diverse AI tasks
• Strong understanding of model evaluation metrics and methodology development
• Excellent communication skills and ability to present complex technical concepts clearly

Preferred Experience

• Publication record in top-tier AI/ML conferences (NeurIPS, ICLR, AAMAS, ICML)
• Experience applying AI to scientific domains such as drug discovery, materials science, chip design, or mathematical reasoning
• Experience working with vision-language models and multimodal architectures
• Demonstrated success in developing efficient small language models for specialized tasks
• Research experience in open-endedness, including emergent behaviors, auto-curriculum learning, or open-world agent systems for design of experiments, hypothesis generation.
• Background in computational chemistry, physics, electrical engineering, or mathematics
• Experience with Kubernetes and containerized workflow orchestration
• Familiarity with ML infrastructure tools like Ray, Hydra, or MLflow
• Knowledge of interpretability methods and system analysis approaches
• Experience with domain adaptation for specialized scientific applications
• Open-source contributions to AI research or tooling
• Experience in developing custom GPU accelerated pipelines.
• Experience optimizing large-scale models for inference and deployment.

What We Offer

• Opportunity to work on cutting-edge AI research with real-world impact
• Access to substantial computational resources for large-scale experimentation
• Collaborative environment with top researchers and engineers
• Flexibility to pursue novel research directions within the company's mission
• Competitive compensation and benefits package

Join us in shaping the future of intelligent systems and their applications across diverse scientific domains.

Job Location: Chennai, Bangalore, Noida, Hyderabad

As a Gen AI Researcher, you will develop and optimize domain specific large language models (LLMs) and small language models (SLMs) to address unique domain specific challenges and deliver innovative solutions. Your role includes creating advanced SLMs and LLMs for specific domains, focusing on supervised fine tuning, reinforcement learning from human feedback (RLHF), pre and post training, evaluation, and multi-modalities.

Key Responsibilities:

• Conduct cutting edge research in the field of NLP and develop advanced SLMs and LLMs tailored to domain specific applications.
• Design, implement, and optimize language models to solve domain specific problems effectively and efficiently.
• Analyze and preprocess large datasets to ensure high-quality input for training SLMs and LLMs.
• Design and Evaluate the performance of language models using appropriate metrics and benchmarks, and iterate on improvements.
• Developing and implementing methods that extend and improve model capabilities, reliability, and safety
• Work closely with cross functional teams, including domain experts, data engineers, and software engineers, to integrate language models into the production.
• Publish research findings in top tier conferences and journals, and communicate results to both technical and non technical stakeholders.
• Keep abreast of the latest advancements in the field of NLP, ML, and AI, and apply relevant techniques to ongoing projects.

Qualifications:

• Ph.D. in Computer Science, Computational Linguistics , Data Science, Artificial Intelligence, or a related field with a focus on NLP or ML.
• Bachelor's or Master’s degree in Computer Science, Computer Engineering, relevant technical field.
• At least 1 year of experience in developing and optimizing SLMs and LLMs, focusing on foundation model training, supervised fine tuning, reinforcement learning from human feedback (RLHF).
• Solid understanding of various fine-tuning techniques like full fine tuning, PEFT techniques like LoRA, QLoRA and the strategy to adopt for various objectives
• Have solid ML and RL software engineering and scientific research skills
• Have produced novel research related to fine tuning SLMs / LLMs or improving upon pretrained SLMs / LLMs
• Proven experience in Gen AI libraries / frameworks, including but not limited to LangChain, LangGraph, LlamaIndex and LangSmith.
• At least 5 years of Research experience in one or more of these areas: NLP, speech, computer vision, Multimodal, machine learning, deep learning, or related fields.
• Proficiency in programming languages such as Python, and experience with NLP/ML frameworks like TensorFlow, PyTorch, and Hugging Face, as evidenced by released code (e.g. on GitHub) or elsewhere
• Familiarity with domain specific applications and the ability to translate domain knowledge into effective language models.
• Knowledge of Responsible AI practices and compliance with relevant laws is a plus.
• Industry experience with large-scale data processing, distributed computing, or cloud platforms.
• Proven understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms is a plus.
• Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to diverse audiences.
• Ability to work collaboratively in a team environment and contribute to a positive and productive work culture.

About Us:

We're a pioneering AI consulting firm dedicated to harnessing the power of artificial intelligence. Our expertise in Large Language Models (LLMs) enables us to offer unparalleled solutions.

Job Responsibilities:

• Develop and implement cutting-edge language models using transformer architectures and reinforcement learning techniques.
• Conduct research and experimentation to improve model accuracy, efficiency, and scalability.
• Collaborate with cross-functional teams to integrate AI models into practical business solutions.
• Utilize advanced data analytics and machine learning techniques to extract valuable insights from large datasets.
• Mentor junior team members and foster a culture of innovation.
• Presentation of findings and progress to stakeholders.

Requirements:

• Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Ph.D. preferred.
• 5+ years of experience in data science or AI research, with a focus on language modeling and reinforcement learning.
• Strong proficiency in Python and familiarity with AI/ML frameworks.
• Demonstrated experience with transformer models and NLP techniques.
• Solid understanding of reinforcement learning algorithms and their applications.
• Experience with large-scale data processing and analysis.
• Excellent problem-solving skills and ability to work independently.

Benefits:

• Flexible remote position.
• Opportunity to work at the forefront of AI technology.
• Engage in meaningful projects with real-world impact.
• Culture of continuous learning and professional development.

For Application:

Please submit your resume and a cover letter detailing your experience with LLMs.

We are seeking a skilled Data Scientist to join our team and drive innovation in Multimodal Large Language Models and Agentic Workflows.

In this position, you'll contribute across the full LLM lifecycle, from data collection and post-training to evaluation and benchmarking. You will work closely with our data engineering teams to translate data into client-facing insights.

You will have the freedom to publish scientific work and contribute to open-source initiatives.

Key Responsibilities

• Analyze existing workflows and data pipelines to extract insights, identify areas of improvement, and propose recommendations.
• Collaborate with internal teams and clients to operationalize findings.
• Specialize in one of the following focus areas:
• Data: Collection, curation, and synthetic data creation
• Modeling: Multimodal post-training and agentic workflow creation
• Evaluation: LLM and Agent benchmarking and performance analysis

Required Skills and Qualifications

To succeed in this role, you should have:

• Strong communication and collaboration skills across technical and non-technical audiences.
• The ability to work autonomously, self-motivated, ambitious.
• A client-facing mindset: active listening, clear articulation of findings and recommendations.
• A willingness to help upskill teammates in data science and generative AI fundamentals.

Benefits

We offer a dynamic work environment that fosters creativity and growth. As a member of our team, you can expect:

• Mentorship and professional development opportunities.
• A collaborative and inclusive team culture.
• A comprehensive benefits package, including health insurance and retirement plans.

About us:

We are a leading AI company that is accelerating the advancement and deployment of powerful AI systems. We help our customers in two ways:

• Working with world-renowned AI labs to advance frontier model capabilities.
• Leveraging that work to build real-world AI systems that solve mission-critical priorities for companies.

In this role, you will be working on projects to fine-tune large language models using your strong analytical and English comprehension skills. You should have a solid foundation in mathematics, particularly at the level expected in PhD-level programs.

You will need to break down complex mathematical concepts into simple, clear explanations and work efficiently. The projects will also help you learn how to leverage AI to be a better analyst. This is your chance to future-proof your career in an AI-first world.

• Design and solve challenging math problems to probe the limitations of large language models.
• Develop high-quality, step-by-step solutions with clear and rigorous reasoning.
• Collaborate with LLM researchers to align problem types with evaluation goals, particularly in areas where models commonly struggle.
• Contribute to defining new evaluation benchmarks based on Mathematics curricula spanning early undergraduate to PhD-level topics.

To apply, you must have a qualification in a relevant field such as Mathematics, Applied Mathematics, Statistics, or a related subject. You should also have good research and analytical skills, the ability to provide constructive feedback and detailed annotations, creative thinking abilities, excellent communication and collaboration skills, and self-motivation.

• Qualification: Candidates pursuing a Ph.D./Postdoctoral degree in Mathematics, Applied Mathematics, Statistics, or a related field are eligible to apply.
• Analytical Skills: Good research and analytical skills.
• Feedback Skills: Ability to provide constructive feedback and detailed annotations.
• Creative Thinking: Creative and lateral thinking abilities.
• Communication: Excellent structured communication and collaboration skills in a remote setting.
• Independence: Self-motivated and able to work independently in a remote setting.

As a freelancer with us, you will have the opportunity to work on cutting-edge AI projects with leading LLM companies. You may also have the potential for contract extension based on performance and project needs.

• Work in a fully remote environment.
• Opportunity to work on cutting-edge AI projects with leading LLM companies.
• Potential for contract extension based on performance and project needs.