12,173 AI Researcher jobs in India

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 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.

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.

Job Location: Chennai, Bangalore, Noida, HyderabadAs 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 safetyWork 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 Lo RA, QLo RA and the strategy to adopt for various objectivesHave solid ML and RL software engineering and scientific research skillsHave produced novel research related to fine tuning SLMs / LLMs or improving upon pretrained SLMs / LLMsProven experience in Gen AI libraries / frameworks, including but not limited to Lang Chain, Lang Graph, Llama Index and Lang Smith.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 Tensor Flow, Py Torch, and Hugging Face, as evidenced by released code (e.g. on Git Hub) or elsewhereFamiliarity 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.