Member of Technical Staff, Model Serving

CohereSan Francisco, CA
259d

About The Position

Our mission is to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what's best for our customers. Co is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products. Join us on our mission and shape the future.

Requirements

  • Experience with serving ML models in production.
  • Experience designing, implementing, and maintaining a production service at scale.
  • Strong intuition for system behavior and resource estimation under different workloads.
  • Familiarity with inference characteristics of deep learning models, specifically, Transformer based architectures.
  • Familiarity with computational characteristics of accelerators (GPUs, TPUs, and/or Inferentia), especially how they improve inference latency and throughput.
  • Strong understanding or working experience with distributed systems.
  • Experience in performance benchmarking, profiling, and optimization.
  • Experience with cloud infrastructure (e.g. AWS, GCP).
  • Experience in Golang (or other languages designed for high-performance scalable servers).

Responsibilities

  • Develop, deploy, and operate the AI platform delivering Co's large language models through easy to use API endpoints.
  • Serve optimized LLM models to production in low latency, high throughput, and high availability environments.
  • Interface with customers and create customized deployments to meet their specific needs.
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