Senior Technical Program Manager (Machine Learning Infrastructure)

• 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
• (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
• 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
• If some of the above - other than the ML Infrastructure experience - doesn’t line up perfectly with your experience, we still encourage you to apply! If you consider yourself a thoughtful worker, a lifelong learner, and a kind and playful team member, Cohere is the place for you
• If any of the above doesn’t line up exactly with your experience, we still encourage you to apply

Key responsibilities

• Manage the program portfolio covering inference, efficiency, serving, and endpoints to ensure scalability for a rapidly expanding user base.
• Lead the end-to-end coordination and execution across the program, focusing 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 the needs of internal and external users of the models.