Machine Learning Systems Engineer

About the Role

Join RelationalAI to revolutionize enterprise AI by contributing to the ScalarLM open-source framework, operating at the critical intersection of high-performance computing, distributed systems, and cutting-edge LLM research.

Responsibilities

• Contribute code and performance improvements directly to the open-source ScalarLM project.
• Develop and optimize distributed training algorithms for large language models (LLMs).
• Implement high-performance inference engines and apply optimization techniques.
• Work on the integration between vLLM, Megatron-LM, and HuggingFace ecosystems.
• Build tools for seamless model training, fine-tuning, and deployment.
• Optimize performance across advanced GPU architectures.
• Research and implement new techniques for self-improving AI agents.

Requirements

• 3+ years of experience in machine learning engineering or research.
• Proficiency in both C/C++ and Python programming languages.
• Deep understanding of High Performance Computing (HPC) concepts, including MPI programming and optimization.
• Solid understanding of gradient descent, backpropagation, and transformer architectures.
• Experience with large-scale distributed training frameworks (e.g., Megatron-LM, DeepSpeed).
• Familiarity with inference optimization frameworks (e.g., vLLM, TensorRT).

Nice-to-Haves

• CUDA/ROCm programming experience.
• Experience with Bulk Synchronous Parallel (BSP) computing models.
• Publications in machine learning research.
• Experience with containerization (Docker, Kubernetes) and cluster management.
• Background in systems programming and performance optimization.