Website:
dreamvu.ai
Job details:
About the RoleDreamVu builds data infrastructure for Physical AI — capturing, processing, and annotating real-world multimodal data used to train humanoid robots and embodied AI systems.
We are looking for a VP of Engineering to own the infrastructure that powers our data operations. This is a pure engineering leadership role — focused on reliability, scalability, throughput, and cost efficiency. The ideal candidate has run large-scale data or cloud infrastructure in a demanding production environment and is looking to apply that experience to one of the most consequential data problems in AI.
What You Will OwnThe role spans three areas:
Pipeline operations — end-to-end ownership of the data pipeline from raw sensor capture through pre-processing, automated pre-annotation, and human-in-the-loop annotation and QA. Full pipeline details are shared during the interview process.
Production integration — when new pipeline components are developed, this role owns their integration, hardening, and stabilisation into the production system.
Engineering infrastructure and tooling — monitoring and alerting, QA frameworks, dataset management, workflow tooling, and the operational documentation that supports consistent delivery.
Responsibilities- Own pipeline reliability, throughput, and quality SLAs end-to-end
- Build and lead the engineering and operations team as data volume scales
- Define and manage the process by which new pipeline components become stable production systems
- Maintain a clear view of technical debt and a plan to address it
- Establish engineering practices — code standards, review processes, incident response, documentation
- Translate data capture roadmaps into pipeline capacity plans and delivery schedules
- Drive continuous improvement in cost, throughput, and manual effort across the pipeline
- Maintain visibility into pipeline health for the team and for leadership
- Coordinate with capture operations ahead of new data collection campaigns
What We Are Looking For- 8+ years in engineering roles, including at least 3 years in an engineering leadership position - ideally in cloud services, data infrastructure, or large-scale platform engineering
- Background in running high-throughput, high-availability production systems — experience with cloud-scale data pipelines (AWS, GCP, or Azure) is a strong signal
- Strong operational instincts — you define SLAs, instrument systems proactively, and treat instability as an engineering problem to be solved
- Solid Python fundamentals and comfort working within and extending an existing codebase
- Experience building and managing small, high-ownership engineering teams under delivery pressure
- Strong planning and communication skills — comfortable holding accountability across engineering and operations, and reporting status clearly to the CEO
Bonus- Cloud data platform engineering (AWS / GCP / Azure)
- High-throughput pipeline operations
- Video or multimodal data at scale
- Annotation platform operations
- Pipeline orchestration tools
- Early-stage engineering leadership
What Makes This Role DistinctiveDreamVu's data pipeline processes multimodal sensor streams at scale across a complex, multi-stage workflow. The engineering challenges here — throughput, reliability, cost efficiency, and quality at volume — are the same class of problems found in demanding cloud data platforms, but applied to a domain at the frontier of AI. For an infrastructure engineer looking for a high-ownership role with meaningful scope, this is an unusually substantive opportunity.
Location & StructureThis role is based at our Hyderabad R&D centre, with regular coordination with the Philadelphia founding team. Reports to the CEO.
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