Lead Technical Program Manager (AI Platform)

Location: Sunnyvale, California, USA; the role is also stated to be based in the London office with a hybrid working policy.

Company

hirify.global develops AI platform technologies for autonomous vehicle models, including the infrastructure and tooling used to train, iterate, and deploy models on vehicles.

What you will do

• Build, coach, and grow a small technical program management team.
• Partner with AI Platform leadership to plan, prioritise, and deliver data, compute, developer tooling, training technology, compute management, and embedded/inference programs.
• Lead flagship technical programs and maintain delivery partnerships with engineering leadership.
• Establish planning cadences, governance, KPIs, dashboards, escalation paths, and operational reviews.
• Coordinate ML/research, infrastructure, embedded/on-vehicle, engineering, cloud, and vendor teams while managing dependencies, risks, and trade-offs.
• Connect platform delivery to developer velocity, compute efficiency, cost, training performance, and inference performance.

Requirements

• 8+ years of hands-on technical program management experience in platform or infrastructure programs, including people and process leadership.
• Experience building, coaching, and growing high-performing teams or scaling a program function.
• Strong understanding of machine learning, GPUs, large-model training and inference, compute, and orchestration.
• Experience with embedded or on-vehicle systems, inference optimisation, model deployment to constrained edge compute, and hardware-software trade-offs.
• Familiarity with Kubernetes, Ray, Flyte, Docker, Azure, Python, compute management, ML platform tooling, and model-development workflows.
• Ability to lead cross-functionally, apply systems thinking, define measurable outcomes, and communicate with clarity in ambiguous environments.

Nice to have

• Experience with a large-scale ML or compute platform used by hundreds of engineers and researchers.
• Embedded/edge inference, on-device model optimisation, or hardware-aware ML experience.
• Background in autonomous vehicles, robotics, or large-scale ML/infrastructure programs.
• An engineering or computer science degree, or prior engineering experience.

Culture & Benefits

• Hybrid work combining time in offices and workshops with time working from home.
• Office collaboration supports innovation, relationships, culture, and learning.
• AI Agents such as Cursor, Claude, and Codex are used to accelerate execution.

Hiring process

• Submit a CV in DOCX, PDF, RTF, TXT, MD, or HTML format.
• The CV is used to prefill as much of the application form as possible.