Software Developer, Robotic Data & Deliveries

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.

The Role

We are hiring a Software Developer to build — end to end — the internal products and tooling that turn Mecka’s ego-data pipeline into fast, reliable, at-spec dataset deliveries to frontier AI labs. This is a 0 1 role: you’ll take a rough delivery problem, design the interface and the system behind it, ship a first version fast, and iterate with the people using it.

You’ll own whole surfaces rather than a single layer — the review and QA UIs our labeling and delivery teams live in, the dashboards sales uses to track a delivery, the export and validation logic underneath, and the data plumbing that ties it together. Front-end one week, data pipeline the next, a scrappy internal tool the week after.

You’ll work hand-in-hand with the Delivery Operations team — including our Robotic Data & Deliveries TPM — turning recurring delivery pain into products people actually want to use. When a workflow is slow, manual, or fragile, you’re the one who builds the thing that fixes it.

Ideal background: full-stack or product engineering with a track record of building tools and products 0 1. Comfort with data and large-dataset systems is a strong plus, but breadth, product sense, and speed matter more than depth in any one stack.

What you will be doing:

Internal Products & Delivery Tooling

• Design and build the internal products our teams use every day — dataset review and QA interfaces, delivery-tracking dashboards, data viewers, and the workflows that string them together — owning both the UI and the logic behind it.
• Turn one-off scripts and manual steps into real tools with a usable interface, so delivery, sales, labeling, and QA move faster without engineering babysitting.

0 1 Product Building

• Take fuzzy problems from a conversation to a shipped v1 quickly, then iterate with real users — internal teams today, and the experience AI-lab customers touch when they receive a delivery.
• Make pragmatic build-vs-buy and scope calls; ship the 80% that unblocks people now and harden it as it proves out.

Data & Platform Plumbing

• Build the pipelines and APIs that package, validate, index, and serve ego datasets — the systems that make petabyte-scale video and sensor data usable for delivery, labeling, QA, and model training.
• Keep the tools you ship reliable and honest about data quality, so problems get caught before a dataset reaches a customer.

Who You Are

• 3+ years building software as a full-stack or product engineer (or equivalent impact) — you’re comfortable owning a feature from UI to data.
• Fluent in a modern front-end stack (e.g., TypeScript/React) and at least one backend language (e.g., Python, Node, Go).
• A demonstrated 0 1 builder — you’ve taken tools or products from nothing to in-use, and you thrive in ambiguity without a detailed spec.
• Strong product sense and a bias to ship: you scope ruthlessly, get a v1 in front of users, and iterate.
• Comfortable working directly with data — querying databases (e.g., SQL, MongoDB) and reshaping or validating datasets.

Even better if you have:

• You’ve been an early or founding engineer, built internal tools teams loved, or shipped side projects end to end.
• You have real UX/design instincts — your tools are fast, clear, and pleasant to use, not just functional.
• You think in terms of the user, clean interfaces, and shipping — and you write maintainable code with strong ownership.
• Exposure to video/media or large-dataset systems (ingestion, storage, metadata/search, ETL) is a plus, not a requirement.

Why This Role

• Own real surface area from day one — build the products that power petabyte-scale robotics datasets and the deliveries frontier AI labs depend on.
• Maximum breadth: front-end, back-end, data, and product, on problems that are still greenfield.
• High ownership and direct impact across delivery, operations, sales, and research — paired tightly with the TPM who owns the delivery programs you build for.

A Note on Applying

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