Technical Program Manager, Infrastructure & Capacity Management

Cohere•New York, NY

32d

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. 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! We're seeking an experienced Technical Program Manager to join Cohere's Technical Program Management team. We need someone with curiosity, drive, independence, and leadership, who has hands-on experience launching LLM models or enterprise-grade software onto cloud platforms. In return, you'll have the unique opportunity to shape Cohere's operations, collaborate with leading minds in the LLM space. You will get a chance to create extremely high-impact contributions to our fast-growing company, product and culture. This role is open to candidates based on the East Coast and within an hour of GMT.

Requirements

You have 5+ years of experience as a Technical Program Manager
You have 3+ years working with infrastructure teams, and have a solid understanding of the challenges with project and program management in this space
You know how to use Github & Grafana, can read Terraform, and are generally comfortable with onboarding and diving into new technologies
You have practical experience, either in a hands-on role or as a TPM, with full lifecycle management of compute resources (GPUs, CPUs, VMs etc.)
You have a blend of experience working in the intersection of software, hardware, and machine learning - particularly with GPUs used for ML training and inference
You have hands-on experience with coordinating large-scale, company-wide programs within a deeply technical space
You have worked in highly dynamic, fast-paced environments, requiring striking a balance between speed and structure

Nice To Haves

(bonus) You have experience with managing projects and programs related to serving and efficiency of LLMs
(bonus) You have past experience in a technical role, such as infrastructure engineer, software engineer, machine learning engineer etc.

Responsibilities

Coordinate with internal and external teams (cloud providers, GPU manufacturers etc.) to manage the full lifecycle of compute resources, with a heavy emphasis on GPUs
Lead end-to-end programs within the infrastructure space from planning and execution to cross-functional coordination and stakeholder management
Collaborate directly with technical and non-technical teams to set, track, and manage timelines, deliverables, budgets, scope etc.
Manage various overlapping projects and programs, ruthlessly prioritizing asks, to ensure that the company's top priorities are met
Work with leadership on anticipating and planning capacity needs across the company, and turning these needs into practical execution plans on how capacity is allocated, tracked, and managed
Deliver clear, timely, and consistent updates across engineering, leadership, and non-technical teams on the monthly container releases and wider model launches.

Benefits

An 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
ï¸ 6 weeks of vacation (30 working days!)

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