Build internal products and tooling for dataset deliveries in a fast-paced robotics AI startup.
Posted by employer 1 week ago
First seen on Joblaze 2 days ago
Last verified on the company career page 11 hours ago
What you'll build
Must have
Nice to have
AI in the day-to-day
Mecka uses artificial intelligence (AI) responsibly to support administrative and efficiency-focused aspects of our recruitment process.
Requirements
Not disclosed in this posting: compensation, work arrangement, visa sponsorship.
Joblaze summary
In this role, the Software Developer will focus on creating internal tools and products that streamline Mecka AI's dataset delivery processes for robotics and AI labs. Proficiency in both front-end technologies like TypeScript and React, as well as back-end languages such as Python or Node, is essential, alongside a strong ability to build products from the ground up. This position is ideal for someone with at least three years of experience in full-stack or product engineering, particularly those who thrive in ambiguous environments and have a knack for user-centric design.
Joblaze insights
Quick facts
From the original posting
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.
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.
• 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.
• 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.
• 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.
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