AI Research Scientist

About the Role

We are looking for a highly experienced AI Research Scientist to join our Bengaluru team, focusing on pioneering work in Generative AI, Large Language Models (LLMs), multimodal AI, and computer vision technologies. This role requires building and refining large-scale AI models and collaborating closely with engineering teams to deploy scalable AI solutions.

Key Responsibilities

• Translate and adapt leading AI research publications into functional prototypes and production-capable models.
• Design and execute experiments aimed at enhancing model effectiveness through fine-tuning, prompt engineering, architecture adjustments, and thorough evaluation.
• Lead the development and management of training and testing data, including generation of synthetic datasets, annotation processes, and benchmark setup.
• Work collaboratively with engineering and product teams to incorporate AI innovations into scalable systems.
• Keep abreast of the latest AI research trends and actively participate in planning and innovating research agendas.
• Maintain detailed records of experiments and technical outcomes; contribute to patents, comprehensive reports, and build reusable research resources.
• Promote best practices in experiment reproducibility, benchmarking, and ethical AI research standards.

Required Qualifications and Skills

• In-depth knowledge of Large Language Models, Generative AI, multimodal AI, and computer vision.
• Proven ability to implement cutting-edge AI research from major conferences and journals.
• Strong command of Python programming and proficiency with AI/ML frameworks such as PyTorch, TensorFlow, or JAX.
• Experience utilizing tools like Hugging Face Transformers, Diffusers, MLflow, TensorBoard, or equivalent machine learning utilities.
• Familiarity with distributed model training platforms including DeepSpeed, FSDP, or Horovod.
• Expertise in model optimization methods like quantization, pruning, and knowledge distillation.
• Competence with data management and annotation technologies such as DVC, Apache Arrow, or Label Studio.
• Strong grasp of evaluation metrics, benchmarking techniques, experimental design, and reproducible AI research methodologies.

Educational and Professional Background

• Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or related specialization.
• Extensive experience in AI research, deep learning, and development of advanced AI technologies.
• Demonstrated accomplishments in creating AI prototypes, research models, or scalable production systems.
• Contributions to AI research via publications, patents, or participation in open-source projects are favorable.

Preferred Traits

• Analytical aptitude and strong problem-solving skills.
• Research-focused approach with attention to reproducibility and experimentation rigor.
• Excellent teamwork abilities to engage effectively with research, engineering, and product groups.
• Outstanding skills in technical writing and documentation.