ML Researcher, Foundational Models

The role

You will drive open-ended research on architecture, optimization, scaling behavior, and training stability for next generation foundational models. You will design and execute ablations and translate research findings into proposals for production training runs.

What you will do

• Drive open-ended research on architecture, optimization, scaling behaviour, training stability, and post-training recipes.
• Design and execute ablations at scales that inform large-run decisions.
• Run pre-training experiments end-to-end.
• Translate research findings into concrete proposals for the next training run.
• Work with infrastructure and data teams.
• Read broadly, write internally, and publish externally when the work merits it.

Required qualifications

• PhD in Machine Learning, Computer Science, or a closely related field (or in the final stages of completion).
• 3+ years of research experience post-PhD (or equivalent depth).
• First-author publications at top-tier ML venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, or COLM.
• Hands-on experience pre-training transformer-based language models from scratch, ideally at 7B+ parameters.
• Meaningful contributions to the open-source LLM ecosystem.
• Fluency in PyTorch.
• Comfort with distributed training.
• Strong intuition for experimental design.

Nice to have

• Work on novel architectures (mixture-of-experts, state-space models, hybrid architectures) or non-trivial modifications to standard transformers.
• Experience with multilingual or multimodal pre-training.
• Research contributions in post-training (RLHF, RLVR, distillation, reasoning models).
• A track record of taking a research idea from prototype to a capability that shipped.

About the company

Sarvam is building the bedrock of Sovereign AI for India by developing a full-stack sovereign AI platform across research, models, infrastructure and applications. The company is backed by Lightspeed, Peak XV, and Khosla Ventures.