обновлено 3 дня назад
Technical Program Manager, Data Operations (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Technical Program Manager, Data Operations (AI): Coordinating end-to-end data and annotation operations across data science, ML, engineering, and external suppliers with an accent on intake, estimation, scheduling, execution, QA, and stakeholder alignment. Focus on improving annotation workflows, managing delivery risks and suppliers, enabling self-serve users, and automating reporting while solving complex coordination challenges.
Location: Hybrid role based in the London, United Kingdom or Leonberg, Germany office, combining office and workshop time with working from home.
Company
develops Embodied AI software and foundation models for mapless, hardware-agnostic automated driving systems.
What you will do
- Own data and annotation requests end to end, including intake, definition, estimation, scheduling, execution, and QA.
- Align stakeholders on goals, success criteria, missing inputs, trade-offs, risks, and escalation paths.
- Coordinate engineering and data science or ML teams to estimate work and sequence tickets.
- Coordinate external annotation suppliers across onboarding, label guides, task launch, QA, and delivery tracking.
- Support and troubleshoot internal self-serve users across the annotation tool chain.
- Improve intake, ticketing, reporting, and workflow automation while removing blockers and maintaining delivery visibility.
Requirements
- Around 3 or more years of experience in program, delivery, or operations coordination.
- Strong stakeholder management skills and the ability to create clarity from ambiguous requests.
- Technical fluency sufficient to coordinate with engineers and data science or ML teams and reason about data and pipelines.
- Proactive risk and issue management, clear escalation, structured execution, and frequent communication.
- Ability to influence without authority, build trust with teams and suppliers, and think in terms of systems and outcomes.
- Ability to work in a hybrid arrangement from the London or Leonberg office.
Nice to have
- Experience with data operations, annotation or labelling workflows, or external vendor management.
- Experience with Jira or similar tools and workflow automation.
- Exposure to ML or data pipelines, autonomous driving, or robotics.
Culture & Benefits
- Hybrid working combining collaboration in offices and workshops with working from home.
- Inclusive, diverse, fair, and respectful working environment.
- Support for interview accommodations and adjustments.
- Culture focused on learning, collaboration, high standards, and solving complex problems.
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