Lead Member of Technical Staff, Inference Infrastructure

Cohere

Toronto

Hybrid

CAD 130,000 - 160,000

Full time

14 days+

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Benefits offered by this job

Open and inclusive culture
Weekly lunch stipend
Full health and dental benefits
100% Parental Leave top-up
Personal enrichment benefits
Remote-flexible work
6 weeks of vacation

Job summary

Cohere in Toronto is seeking a Lead Member of Technical Staff to oversee the technical direction of AI platforms, focusing on deploying large language models and ensuring high availability. Candidates should have over 8 years of experience in engineering, particularly in scalable systems with Kubernetes. Key responsibilities include mentoring engineers, collaborating on architecture, and guiding deployment strategies. Benefits include a remote-flexible work environment, comprehensive health coverage, and 6 weeks of vacation.

Qualifications

  • 8+ years of engineering experience running production infrastructure at a large scale.
  • Demonstrated experience leading architecture and design of distributed systems.
  • Deep expertise in Kubernetes development and support.

Responsibilities

  • Lead the design of high-performance machine learning systems.
  • Drive architecture and strategy for deploying optimized NLP models.
  • Mentor engineers to raise technical standards.

Skills

Engineering experience in production infrastructure
Technical leadership
Kubernetes systems design
Multi-cloud services experience
Linux server management
Collaboration and communication
Mentoring engineers
Proficiency in Golang or C++

Job description

Overview

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.

Cohere 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!

Role

Why this role? Are you energized by leading the design of high-performance, scalable and reliable machine learning systems? Do you want to set technical direction and help shape the next generation of AI platforms powering advanced NLP applications? We are looking for a Lead Member of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere\'s large language models through easy to use API endpoints. In this role, you will provide technical leadership across multiple teams, driving the architecture and strategy for deploying optimized NLP models to production in low latency, high throughput, and high availability environments. You will serve as a key point of contact for customers, leading the design of customized deployments to meet their specific needs, and mentoring engineers to raise the technical bar across the team.

You may be a good fit if you have
  • 8+ years of engineering experience running production infrastructure at a large scale, with a track record of technical leadership
  • Demonstrated experience leading the architecture and design of large, highly available distributed systems with Kubernetes and GPU workloads on those clusters
  • Deep expertise with Kubernetes dev and production coding and support, including setting team-wide standards and best practices
  • Extensive experience across GCP, Azure, AWS, OCI, and multi-cloud on-prem / hybrid serving environments, with the ability to guide strategic infrastructure decisions
  • Proven ability to lead the design, deployment, support, and troubleshooting of complex Linux-based computing environments at scale
  • Experience owning compute/storage/network resource and cost management at an organisational level, including optimisation strategies
  • Exceptional collaboration and communication skills, with experience mentoring engineers and leading cross-functional initiatives to build mission-critical systems
  • The grit and adaptability to both solve and guide others through complex technical challenges that evolve day to day
  • Strong expertise in the computational characteristics of accelerators (GPUs, TPUs, and/or custom accelerators), and how to leverage them to drive latency and throughput improvements at scale
  • Deep knowledge of distributed systems, with experience establishing patterns and practices across engineering teams
  • Proficiency in Golang, C++ or other languages designed for high-performance scalable servers, with the ability to set coding standards and conduct senior-level technical reviews

We encourage applicants even if not all align. We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.

Benefits

Full-Time Employees At Cohere Enjoy These Perks

  • Open and inclusive culture and work environment
  • Work closely with a team on the cutting edge of AI research
  • Weekly lunch stipend, in-office lunches & snacks
  • Full health and dental benefits, including a separate budget to take care of your mental health
  • 100% Parental Leave top-up for up to 6 months
  • Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
  • Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
  • 6 weeks of vacation (30 working days)
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