Machine Learning Engineer - GPU Clusters

What You'll Do :

• Design and run training and fine-tuning pipelines for large vision-language models on GPU clusters.

• Build multimodal data pipelines ingestion, filtering, deduplication, synthetic generation, and quality assurance.

• Implement and experiment with new architectures and training techniques from research.

• Build evaluation harnesses, benchmarks, and automated regression tracking.

• Optimise models for inference quantisation, batching, and serving infrastructure.

• Build robust pipelines and integrations that put vision model capabilities in the hands of end users.

• Translate real-world problems into well-scoped ML tasks with the right data and evaluation strategy.

• Work directly with clients to understand their use cases document processing, visual search, form extraction and own the solution end to end.

• Build production-grade systems on top of Sarvam Vision and open-source models: multimodal pipelines, retrieval-augmented workflows, and structured output extraction.

• Debug and improve deployed solutions latency, accuracy, edge cases, and integration with client infrastructure.

What We're Looking For :

• Strong Python and PyTorch comfortable reading and modifying model internals.

• Hands-on experience training or fine-tuning large models, including debugging broken runs.

• Experience building data pipelines at scale.

• Solid grounding in transformer architectures and modern training techniques.

• Comfort with ambiguity the roadmap is not fully pre-specified.

• Strong focus on secure coding practices, code quality, and system reliability.