Technical Program Manager, Robotic Data & Deliveries

Mecka•Richmond Hill, ON
•$150,000 - $200,000

About The Position

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. The Role Own the program that turns Mecka’s ego-data pipeline into on-time, at-spec dataset deliveries to frontier AI labs. You will sit at the seam between our ego-data sales & delivery team and the engineering that produces the data — driving delivery execution against customer commitments while iteratively building the tooling, standards, and datasets that let us scale from bespoke drops to a repeatable delivery engine. This is a hands-on, senior IC role. You will be equally comfortable running a delivery schedule with a demanding AI-lab customer, writing a script to reshape a dataset or query a pipeline, and defining the spec that makes the next delivery faster than the last.

Requirements

  • 2–5+ years as a TPM, Technical Program/Product Lead, or Data/Delivery Operations lead — ideally in ML/AI data, robotics, or another domain shipping complex technical deliverables to sophisticated customers.
  • Data Delivery Expertise: Hands-on experience taking large, complex datasets or technical deliverables from an internal pipeline to an external customer at spec and on time — with a real feel for data quality, QA, and the failure modes of a delivery pipeline.
  • Hands-On Technical Acumen: Comfortable in the data yourself — querying databases (e.g., SQL, MongoDB), writing scripts (e.g., Python) to reshape, validate, or QA datasets, and prototyping tooling before handing it to Engineering to productionize. You can read a schema and a telemetry dashboard, not just a status report.
  • Senior IC Leadership: Proven ability to lead by influence without direct reports — aligning sales, engineers, and operators around a single delivery schedule and holding them to it in a fast-moving, early-stage environment.
  • Systems & Process Mastery: Skilled at configuring workflow and tracking systems (Jira, Asana, Linear, or similar) and building lightweight process and reporting that brings order to chaotic, high-growth scaling environments.
  • Customer-Ready Communication: Able to represent Mecka credibly to technical AI-lab customers — clear on scope, status, and trade-offs — while keeping internal teams honest about what can actually ship.

Responsibilities

  • End-to-End Delivery Program Ownership: Act as the lead program owner for our highest-value ego-data deliveries. Drive cross-functional execution across Sales, Data Operations, Labeling, and Engineering to ship datasets that meet each customer’s spec, volume, and timeline — owning the master delivery schedule and holding contributors accountable to it.
  • Delivery Tooling & Automation: Iterate on the tooling that packages, validates, and hands off ego datasets. Prototype and build — scripts, QA checks, packaging and manifest tooling, delivery dashboards — then partner with Engineering to harden what works into durable infrastructure. Every delivery should leave the pipeline faster and more automated than it found it.
  • Dataset Quality & Standards: Define and enforce the standards that make an ego dataset "delivery-ready" — completeness, metadata, taxonomy, formatting, and QA gates. Turn recurring delivery pain into reusable specs, checklists, and automated validation so quality is built in, not inspected in.
  • Sales & Customer Delivery Partnership: Partner with the ego-data sales & delivery team to translate customer requirements into concrete delivery plans, and translate pipeline realities back into commitments sales can confidently make. Serve as a senior point of contact on delivery scope, status, and escalations for key AI-lab accounts.
  • Metrics & Reporting: Build data-driven reporting for the delivery function — time-to-delivery, dataset volume and yield, QA pass rates, rework, and SLA adherence. Use fleet- and pipeline-level data to spot bottlenecks and quality trends before they threaten a delivery.
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