Staff ML Platform Engineer – Large Scale Training (LLMOps / MLOps)

Build the Future of Scalable AI at TrueFoundry

At TrueFoundry , we’re redefining how ML teams train, deploy, and scale their models. Our LLMOps and MLOps platform empowers organizations to experiment faster, train large-scale models reliably, and deploy them seamlessly on Kubernetes—with the same muscle as Big Tech.

We're looking for ML Systems Engineers who are passionate about scaling deep learning workloads, optimizing multi-GPU training, and shipping production-grade solutions. If you live and breathe PyTorch, multi-node training, and love solving gnarly infra challenges—this is your place.

What You’ll Work On

• Write clean, modular, and scalable Python code , with a strong emphasis on reliability and performance.
• Build platform for training and finetuning large-scale ML models across multi-GPU, multi-node clusters with PyTorch, Kubeflow, and other orchestration tools.
• Own the infrastructure and code that enables high-throughput, low-latency inference pipelines for state-of-the-art models.
• Build platform for developing, deploying and evaluating agentic applications for our end customers.
• Help shape internal standards and best practices across the engineering team for high-scale ML workloads.

What We’re Looking For

Why Join TrueFoundry?

Flexible hours, learning credits, and the opportunity to work shoulder-to-shoulder with the co-founders (Abhishek & Nikunj).

#J-18808-Ljbffr