Senior Applied AI Researcher

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Applied AI Researcher in India.

This role is designed for a researcher who thrives at the intersection of advanced AI research and real-world enterprise impact. You will work on next-generation GenAI systems tailored for high-stakes, regulated industries where accuracy, explainability, and auditability are critical. The position spans the full research lifecycle, from defining problems and designing experiments to training large-scale models and deploying production-ready systems. You will contribute to multimodal AI, reinforcement learning, and knowledge-grounded systems while leveraging agentic workflows to accelerate discovery. The environment is highly collaborative, bringing together research, engineering, and domain experts to push the boundaries of enterprise-grade AI. This is a high-impact role where research directly translates into deployed systems used by Fortune 500 organizations.

• Own and drive end-to-end AI research programs, from problem definition through production deployment, using agentic AI systems to accelerate experimentation and iteration.
• Design and execute large-scale model training workflows, including pretraining, fine-tuning, reinforcement learning (RLHF, DPO), and post-training optimization.
• Conduct deep analysis of model behavior using diagnostics such as loss curves, gradients, and evaluation metrics to identify and resolve failure modes.
• Develop multimodal AI systems spanning text, images, tables, and structured documents, along with hybrid retrieval and knowledge-based architectures.
• Build and optimize agent-driven data pipelines for large-scale curation, preprocessing, and training data quality management.
• Collaborate with engineering and product teams to compress research-to-production cycles using automated evaluation and CI/CD pipelines.
• Mentor researchers on agentic AI workflows and contribute to internal knowledge systems that scale team-wide learning and innovation.
• Publish research findings and contribute to advancing internal and external AI knowledge ecosystems.

Requirements:

• PhD or Master’s degree in Computer Science, Machine Learning, or a related field.
• 5+ years of experience in AI/ML research with demonstrated production-level research outputs.
• At least 2+ years of hands-on experience building and deploying LLM-based systems.
• Strong experience with full training pipelines, including pretraining, fine-tuning, and post-training model optimization.
• Deep expertise in at least one area such as multimodal learning, reinforcement learning from human feedback, knowledge-grounded generation, or retrieval-augmented systems.
• Experience with distributed training frameworks such as DeepSpeed, FSDP, or Megatron-LM.
• Strong software engineering skills in Python with production-grade coding practices and clean system design.
• Ability to diagnose and resolve model training issues using analytical and experimental approaches.
• Experience working on domain-specific AI systems where evaluation criteria must be defined from scratch is highly preferred.
• Exposure to production AI systems, cloud-native infrastructure, and scalable ML pipelines is a plus.
• Strong intellectual curiosity, problem-solving ability, and ability to work in fast-paced research environments.

Benefits:

• Opportunity to work on cutting-edge enterprise GenAI systems used in regulated, high-impact industries.
• Exposure to advanced AI research areas including agentic systems, multimodal learning, and reinforcement learning.
• Strong collaboration with world-class research, engineering, and domain experts.
• High ownership role spanning research to production deployment.
• Access to large-scale compute environments and modern ML infrastructure.
• Career growth in a fast-evolving AI research organization.
• Opportunity to publish research and contribute to frontier AI innovation.
• Dynamic, innovation-driven environment focused on real-world AI impact.