Technical Product Manager (TPM), Delivery Ops

About Mecka AI

Mecka AI is building the data infrastructure layer for robotics and embodied AI.
We design and operate global systems for data capture, data labeling, and hardware-enabled workflows used by leading AI labs and robotics companies to train and validate humanoid and embodied AI systems.
We work closely with frontier robotics teams to bridge real-world data, simulation, learning-based systems, and deployed hardware.

About Delivery Ops

Delivery Ops turns raw captures into datasets customers can train on. We pull and filter episodes against each customer's spec, run every ship gate (quality, privacy, exclusivity, labels), package and ship the data, and report on what was delivered. As volumes grow into hundreds of thousands of hours per program, the team also owns showing the field what this data looks like and why it matters.

About the role

Customers buy data against a spec, and the spec is only as good as our ability to hit it. You will own how deliveries get planned, gated, and shipped: translating what customers ask for into delivery plans and into the tooling roadmap that makes those plans repeatable.

What you'll do

Spec to plan

Turn customer requirements (hours, diversity caps, environments, formats, label levels) into delivery plans with clear milestones and acceptance criteria.

Forecasting

Use measured yield and gate pass rates to forecast what can ship and when, and flag shortfalls before they become missed dates.

Ship-gate ownership

Define and maintain the gates every delivery passes, and sign off that each batch meets spec.

Tooling roadmap

Write requirements and prioritize the delivery tooling roadmap with Delivery Ops engineering.

Feedback loop

Turn customer issue reports into root causes and verified fixes across capture, QA, and labeling.

What you bring

• 4 to 7+ years in technical product management, technical program management, or data operations.

• Fluent in SQL; you pull and check your own numbers rather than waiting on an analyst.

• Clear writing: specs, acceptance criteria, and forecasts that engineers and customers both trust.

• A record of shipping data or platform products to demanding technical customers.

Even better if you have

• Experience with ML training data, annotation programs, or dataset QA.

• Familiarity with sensor and video data (multi-camera, egocentric, calibration).

If you don't check every box above but believe you can do the job, we encourage you to apply — we're looking for capability and trajectory, not a perfect checklist match.

We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, we will partner with you to meet your needs.

We may use AI-assisted tools to help evaluate applications against the requirements of this role. These tools support our recruiting team in identifying qualified candidates but do not replace human judgment or limit which applications may be reviewed or considered.