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Goliath Partners

Senior Machine Learning Engineer

Goliath Partners
San Francisco, CA $2,000k - $2,000k/yr Full time Posted 2d ago
Artificial Intelligence Cloud Machine Learning Distributed Machine Learning Engineer Machine Learning Machine Learning Engineering Machine Learning Optimization Machine Learning Serving Software Development
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Job Description

The Senior Machine Learning Engineer role at Goliath Partners focuses on bridging ML Infrastructure Engineers to deliver production-ready infrastructure for distributed model training and high-performance inference. The position emphasizes scalable distributed systems, cloud and GPU environments, and performance optimization.

Responsibilities

  • Build and scale infrastructure that powers cutting-edge AI systems, spanning distributed model training through high-performance inference.
  • Develop scalable distributed training and inference infrastructure.
  • Optimize performance, reliability, latency, and throughput across production ML systems.
  • Design and take ownership of production machine learning infrastructure at scale.

Requirements

  • 5+ years of experience in ML Infrastructure, Distributed Systems, or Software Engineering, or equivalent demonstrated expertise.
  • Strong programming skills in Python and C++ or Go.
  • Hands-on experience with PyTorch, JAX, or similar ML frameworks.
  • Experience building scalable distributed training and inference infrastructure.
  • Strong knowledge of Kubernetes, Docker, AWS/GCP, and GPU compute environments.
  • Proven ability to optimize system performance, reliability, latency, and throughput.
  • Demonstrated capability to design and own production ML infrastructure at scale.
  • Experience supporting large-scale LLM or foundation model training.
  • Expertise in CUDA, Triton, NCCL, or GPU performance optimization.
  • Experience with distributed training frameworks such as Ray, DeepSpeed, or Megatron-LM.
  • Contributions to high-performance ML systems or influential open-source infrastructure projects.
  • Experience building infrastructure at leading AI research labs or high-growth technology companies.

Technology Stack

  • Languages: Python, C++, Go
  • ML Frameworks: PyTorch, JAX
  • Infrastructure: Kubernetes, Docker, AWS, GCP
  • GPU/Performance: CUDA, Triton, NCCL
  • Distributed Training: Ray, DeepSpeed, Megatron-LM

Education

  • Bachelor's or Master's degree in Computer Science, Computer Engineering, Mathematics, or a related technical field.
  • PhD in Computer Science, Machine Learning, or Distributed Systems is a plus.
  • Exceptional engineers with demonstrated technical impact and deep systems expertise are strongly encouraged to apply.

Location

San Francisco, CA (onsite)

Compensation

USD 2,000,000 to USD 2,000,000 per year

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