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

Studies show women and candidates from underrepresented groups often only apply when they meet 100% of the listed qualifications, while others apply after meeting 60%. 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.

Inclusive Hiring at Mecka

We are committed to creating an inclusive and supportive candidate experience. Should you require any accommodation whatsoever during the interview process, please inform us without any hesitation. Mecka is dedicated to ensuring equal treatment and opportunity in all phases of recruitment, selection, and employment, in compliance with employment law. We do not discriminate based on gender, race, religion, national origin, ethnicity, disability, gender identity/expression, sexual orientation, veteran or military status, or any other protected category. Mecka is proud to be an equal opportunity employer, fostering a culture of inclusivity and maintaining a work environment that is free from discrimination, harassment, and retaliation.

Use of Artificial Intelligence in Recruitment

Mecka uses artificial intelligence (AI) responsibly to support administrative and efficiency-focused aspects of our recruitment process. This includes activities such as drafting job descriptions, generating interview questions, note-taking and recordings, and supporting sourcing and scheduling workflows. All candidate evaluations, interviews, and hiring decisions are made by members of the Mecka team. While AI tools may assist with screening and assessment, they do not replace human judgment in selection decisions. Our use of AI is intended to streamline routine tasks, improve consistency, and enhance the overall candidate experience. We are committed to upholding principles of fairness, transparency, and accountability in all hiring activities. Mecka regularly reviews its recruitment practices to mitigate bias and to ensure alignment with applicable laws and evolving best practices.