LLM Systems Architect — Bay Area (Onsite)

Harnham

San Francisco (CA)

On-site

USD 450,000 - 550,000

Full time

1 hour ago
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Job summary

Harnham in the Bay Area is seeking a Principal Machine Learning Engineer to design and scale LLM-powered systems and reusable APIs. The role sits at the intersection of research and production, delivering architectures that support chatbots, code generation, and data interaction at enterprise scale.

You will bridge research with production-grade engineering, build agent-based systems and RAG pipelines, and work closely with cloud/SRE teams to ensure robust, scalable solutions.

Qualifications

  • PhD in CS/Math/Stats or related field.
  • Strong experience as an IC in ML engineering.
  • Proven track record in building ML/AI systems in production.
  • Deep understanding of ML fundamentals (NLP/CV).
  • Experience with distributed systems (Ray, Horovod, DeepSpeed, etc.).
  • Strong software engineering and system design fundamentals.
  • Experience owning ML services end-to-end in enterprise environments.
  • Ability to align technical work with business outcomes and communicate with stakeholders.

Responsibilities

  • Design and deploy scalable LLM-powered systems and reusable backend APIs
  • Bridge cutting-edge AI research with production-grade engineering
  • Build agent-based systems, RAG pipelines, and workflow automation tools
  • Develop capabilities across chatbots, text-to-code, and data interaction layers
  • Partner with cloud and SRE teams to deliver robust, scalable architectures
  • Implement distributed systems for training and inference (e.g., Ray, DeepSpeed)
  • Drive best practices for ML systems, deployment, and performance optimization

Skills

IC ML Engineer
Distributed systems
ML deployment
NLP/CV fundamentals

Education

PhD (CS/Math/Stats)

Tools

Ray
Horovod
DeepSpeed
Kubeflow

Job description

Harnham in the Bay Area is seeking a Principal Machine Learning Engineer to design and scale LLM-powered systems and reusable APIs. The role sits at the intersection of research and production, delivering architectures that support chatbots, code generation, and data interaction at enterprise scale.

You will bridge research with production-grade engineering, build agent-based systems and RAG pipelines, and work closely with cloud/SRE teams to ensure robust, scalable solutions.

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