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Senior Staff Machine Learning Researcher - LLM Algorithmic Optimization - D Matrix
ML Engineer
Lead cutting‑edge research on algorithmic optimization for large language models, designing scalable training pipelines and novel techniques using Python, PyTorch, CUDA, and distributed systems.
About the role
Key Responsibilities
- Design and implement advanced optimization algorithms to improve the efficiency and performance of large language models.
- Develop and maintain high‑throughput training pipelines using PyTorch, TensorFlow, and CUDA on multi‑GPU/TPU clusters.
- Conduct rigorous experiments, analyze results, and publish findings in top‑tier conferences or internal knowledge bases.
- Collaborate with hardware and systems teams to co‑design software‑hardware interfaces that maximize compute utilization.
- Mentor senior engineers and researchers, fostering best practices in code quality, reproducibility, and scientific rigor.
Requirements
- Ph.D. or equivalent experience in Machine Learning, Computer Science, or a related field with a focus on large‑scale model training.
- 5+ years of hands‑on experience building and optimizing LLMs using Python, PyTorch or TensorFlow.
- Deep understanding of distributed training frameworks, GPU/TPU programming, and performance profiling (CUDA, NCCL, MPI).
- Proven track record of publishing research or delivering production‑grade ML systems at scale.
- Strong problem‑solving skills, ability to work cross‑functionally, and excellent communication of complex ideas.
Skills
pythonpytorchtensorflowcudac