AI Research Engineer - Generative AI Foundation Models (India)

2-4 years
a month ago
Job Description

Location: Bangalore, Karnataka, India

Type of Job: Full-time

About Krutrim: Building AI computing for the future

Krutrim, a part of the Ola group, is working on creating the AI computing stack of the future. We endeavor to deliver a state-of-the-art AI computing stack that encompasses the AI computing infrastructure, AI Cloud, foundational models, and AI-powered end applications for the Indian market.

Our envisioned AI computing stack can empower consumers, startups, enterprises and scientists across the world to build their end AI applications or AI models. While we are building foundational models across text, voice, and vision relevant to our focus markets, we are also developing AI training and inference platforms that enable AI research and development across industry domains.

The platforms being built by Krutrim have the potential to impact millions of lives in India, across income and education strata, and across languages.

The team at Krutrim represents a convergence of talent across AI research, Applied AI, Cloud Engineering, and semiconductor design. Our teams operate from three locations: Bangalore, Singapore & San Francisco.

Job Description:

We are looking for experienced Generative AI Engineers to train, optimize, scale, and deploy a variety of generative AI models such as large language models, voice/speech foundation models, vision and multi-modal foundation models using cutting-edge techniques and frameworks. In this role, you will conduct advanced research and development to push the boundaries of what is possible with generative AI and language models.


  1. Research, architect, and deploy new generative AI methods such as autoregressive models, causal models, and diffusion models
  2. Refine foundation model infrastructure to support the deployment of optimized AI models with a focus on C/C++, CUDA, and kernel-level programming enhancements
  3. Implement state-of-the-art optimization techniques, including quantization, distillation, sparsity, streaming, and caching, for model performance enhancements
  4. Design and develop novel large language models and corresponding architectures by leveraging transformers, and state-of-the-art architectures
  5. Drive innovations in NLP techniques like text generation, summarization, translation, question answering, etc. enabled by generative models
  6. Integrate and tailor frameworks such as PyTorch, TensorFlow, DeepSpeed, and FSDP for the advancement of super-fast model training and inference
  7. Advance the deployment infrastructure with MLOps frameworks such as KubeFlow, MosaicML, Anyscale, and Terraform, ensuring robust development and deployment cycles
  8. Publish papers at top-tier AI/ML conferences like NeurIPS, ICML, ICLR on new research contributions
  9. Collaborate with engineering teams to productionize research advancements into scalable services and products


  1. Ph.D. or MS with 2+ years of research / applied research experience in LLMs, NLP, CV, Reinforcement Learning, Voice, and Generative models
  2. Demonstrated expertise in high-performance computing with proficiency in Python, C/C++, CUDA, and kernel-level programming for AI applications
  3. Extensive experience in the optimization of training and inference for large-scale AI models, including practical knowledge of quantization, distillation, and LLMOps
  4. Prior experience with large-scale distributed training and fine-tuning of foundation models such as GPT-3, LLaMA2, AlphaFold, and DALL-E
  5. Experience with language modeling evaluation, prompt tuning and engineering, instruction tuning, and/or RLHF
  6. Research contributions in NLP, generative modeling, LLMs demonstrated through publications and products
  7. Strong programming skills and proficiency in Python, TensorFlow/PyTorch, and other ML frameworks and tools
  8. Experience in Information Extraction, Question Answering, Conversational Agents (Chatbots), Data Visualization and/or text-to-image models
  9. Excellent communication and collaboration skills to work cross-functionally with various teams






Conversational Agents
text-to-image models
Generative modeling
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