Lead Member of Technical Staff, Inference Infrastructure in Toronto

Lead Member of Technical Staff, Inference Infrastructure in Toronto

Toronto Full-Time 123750 - 151250 $ / year (est.) Hybrid
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At a Glance

  • Tasks: Lead the design of high-performance AI systems and mentor engineers.
  • Company: Join a cutting-edge AI company passionate about innovation and diversity.
  • Benefits: Enjoy flexible remote work, health benefits, and 6 weeks of vacation.
  • Other info: Collaborative environment with opportunities for personal and professional growth.
  • Why this job: Shape the future of AI and make a real impact in tech.
  • Qualifications: 8+ years in engineering with expertise in distributed systems and Kubernetes.

The predicted salary is between 123750 - 151250 $ per year.

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!

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.

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)

Lead Member of Technical Staff, Inference Infrastructure in Toronto employer: Cohere

Cohere is an exceptional employer that fosters a dynamic and collaborative work culture, making it an ideal place for an Executive Assistant to thrive. With a strong focus on employee growth, we offer generous benefits including a weekly lunch stipend, comprehensive health coverage, and a robust education stipend, all while working in a cutting-edge AI environment in Toronto. Join us to be part of a passionate team dedicated to innovation and meaningful impact in the world of AI.

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Contact Details:

Cohere Recruitment Team

We think you need these skills to ace Lead Member of Technical Staff, Inference Infrastructure in Toronto

Technical Leadership
Machine Learning Systems Design
NLP Applications
Kubernetes
Distributed Systems
GCP
Azure