You'll design and optimize distributed AI systems using Python, PyTorch, CUDA, and related tools, specializing in areas like inference optimization (KV cache, quantization, speculative decoding), large-scale training, post-training (fine-tuning, RLHF, DPO), or evaluation frameworks. Nscale builds a vertically integrated GenAI cloud platform spanning data centers, software, and applications. This hands-on role requires 5+ years in production ML/distributed systems and deep expertise in at least one core area within hyperscaler or AI lab environments.

EPAM Systems★3.8 (703)· London

You'll work with Python, LLMs, and multi-agent orchestration frameworks including LangGraph, CrewAI, and AutoGen to design and deploy Generative AI and Agentic AI solutions. The role involves building RAG pipelines, implementing multi-step agent workflows, and developing production-grade microservices integrated with enterprise systems across multiple industries. You'll apply observability tools like Langfuse and Grafana while working within EPAM's Data & AI Practice, which delivers AI applications that transform client capabilities.