Senior Technical Program Manager, Machine Learning Infrastructure

Cohere is seeking a Senior Technical Program Manager for Machine Learning Infrastructure to manage complex programs and collaborate across teams. Join a leading AI company focused on innovative solutions. Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. 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. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris. Join us!

• •Manage the program portfolio covering inference, efficiency, serving, and endpoints to guarantee that Cohere’s infrastructure continues to scale for a rapidly expanding user base of internal and external users.
• •Lead the end-to-end coordination and execution across the program, with a particular focus on cross-functional collaboration with Modeling and customer-facing teams.
• •Identify pain points and establish processes to ensure that the team can focus on development, while meeting needs of internal and external users of the models, and improving engineering best practices.
• •Build a strong culture around continuous improvement, such as liaising with incident management leads, ensuring that problems are accurately root caused, and that required fixes are provided in a timely manner.
• •Manage various overlapping projects and programs, ruthlessly prioritizing asks, to ensure that the company’s top priorities are met.
• •Collaborate with stakeholders across the company to set, track, and manage timelines, deliverables, budgets, and scope to ensure successful program execution.
• •Deliver clear, timely, and consistent updates across engineering, leadership, and non–technical teams on the progress, plans, and incidents.
• •Act as a strong tactical and strategic partner to the senior leads across your program, whether that be providing low-level tactical support or help answer high-level strategic problems that drives impact at the company-level.

• •A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.
• •Full health and dental benefits, including a separate budget for mental health.
• •RRSP matching, 401K, Pension Scheme.
• •100% Parental Leave top-up for up to 6 months, for either parent.
• •Annual enrichment benefits:
• •Arts & culture, fitness/wellness, quality time, and a workspace improvement credit.
• •Education & learning stipend for conferences, courses, and coaching.
• •6 weeks of paid vacation (30 working days!).
• •Budget for traveling to other offices if you are remote, plus an annual company offsite.

• •5+ years of Technical Program Management experience focusing on Machine Learning Infrastructure, specifically covering areas such as model inference, serving, efficiency, and endpoints design & implementation.
• •In-depth technical knowledge around ML infrastructure design and implementation, as well as engineering best practices, supporting a balance of velocity and structure in rapidly growing organizations.
• •Experience working in a chaotic, fast paced, low structure environment. We need an EPM who is pragmatic, can roll up their sleeves when needed, and can function at the tactical and strategic level to do whatever it takes to make Cohere’s models succeed.
• •(optional, but strongly preferred) Have technical experience in a hands-on capacity. We don’t necessarily need someone who has been working hands-on in a technical role, but the programs are inherently extremely technical. You need to dive into the depths of internal systems, and develop a reputation as a subject matter expert who brings in engineering best practices and the right amount of structure to continuously improve the program.
• •(optional, but preferred) Experience working with ML teams, and a working understanding of how machine learning models are built in order to advocate for both the needs of the infrastructure teams and modeling teams in building scalable, highly performant ML infrastructure.