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.
You will bring intelligence to the devices that capture the world for robot learning. As Mecka's capture network grows, your models will turn advanced computer vision into capabilities that work wherever people collect data, within the limits of real hardware.
You will own the work from model training and evaluation to efficient deployment on embedded devices. Bring strong computer vision, C++, and performance engineering skills to the challenge of delivering accurate results under tight latency, memory, and power constraints.
Train and evaluate computer-vision models for deployment on embedded devices.
Build efficient C++ inference pipelines and integrate them with embedded Linux software.
Optimize models and runtime performance for latency, memory, power consumption, and sustained operation.
Test performance on representative data and hardware, and investigate errors across preprocessing, inference, and integration.
5+ years of experience in machine learning or computer vision, including deploying models on embedded or resource-constrained hardware.
Strong Python and C++ programming skills, including debugging and performance profiling.
Experience training and evaluating computer-vision models with a framework such as PyTorch.
Experience developing on embedded Linux.
Understanding of quantization, model conversion, and inference optimization on CPUs, GPUs, or NPUs.
Ability to evaluate accuracy, false positives, and missed detections across changing lighting, motion, and operating conditions.
Experience with accelerator runtimes, custom operators, or camera and video pipelines.
Experience with dataset curation.
You are ambitious about what you build. You can point to results you personally delivered.
You care deeply about your craft, pursue difficult questions, and learn quickly.
You take initiative and own problems through to results. You work independently, make decisions, and bring others in when needed.
You communicate honestly. You own mistakes, share credit, and help the people around you succeed.
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.
Mecka AI provides large-scale, high-quality human movement video data and labeled datasets to train AI and robotics systems. It builds bespoke multimodal datasets by coordinating a global network to record specific tasks, delivering anonymized, richly annotated videos ready for model training, with participants earning income by filming themselves. Its approach emphasizes tailored, task-specific data and rigorous annotation through a scalable data-collection network, setting it apart from generic data providers. Its goal is to speed up the development and deployment of embodied and autonomous AI by supplying ready-to-use training data for humanoid robotics and other autonomous systems.
Company Size
51-200
Company Stage
Series B
Total Funding
$120M
Headquarters
New York City, New York
Founded
2025
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Robot-data startup Mecka AI has acquired Ottawa social app Thirdspace, according to reporting from BetaKit and a Carleton University alumni profile. Thirdspace co-founder Cedric Osagie is now Mecka's head of mobile capture; the acquisition price was not disclosed. The deal adds consumer-app growth experience to Mecka's effort to expand data collection for robotics.
Mecka AI raises $60M from Sequoia and NVIDIA to pay people to teach robots how humans move. October 8, 2026 * Mecka AI raised a $60 million Series B led by Sequoia, with NVIDIA, M12, Qualcomm, and Samsung. * It pays people to record everyday tasks and sells the motion data to robot developers. * Mecka claims a $100 million run rate; its reported $500 million valuation is unconfirmed. Mecka AI pays people to fold laundry, make coffee, and repair cars while wearing body sensors. The recordings are what it sells. The Toronto- and New York-based startup announced a $60 million Series B led by Sequoia Capital to turn them into training data for humanoid robots. NVIDIA, Qualcomm Ventures, Samsung, and M12, Microsoft's venture fund, joined as new investors, while Kindred, Framework Ventures, and Neo returned. Angels include DoorDash founder and chief executive Tony Xu, former ServiceNow and Snowflake chief executive Frank Slootman, and Milan Kovac, who used to head Tesla's Optimus humanoid robot programme. The round takes Mecka's total funding past $120 million, counting the $60 million Series A led by Framework Ventures, disclosed in June, and an $8 million seed round listed by Dealroom. Mecka's announcement gives no valuation. TechCrunch reported, citing two people with knowledge of the deal, that Sequoia's round values the company at about $500 million. Sequoia declined to comment. Paying humans to teach machines. Mecka was co-founded by Josh Gao, chief executive, Jason Chong, chief technology officer, Mogen Cheng, and Duy Nguyen. None has credentials from a leading AI lab, Fortune noted. Gao and Cheng sold a restaurant payments startup in 2023. Chong joined Coinbase after it bought his crypto startup. Mecka, which is only a couple of years old, pays people to record everyday tasks with smartphones, body sensors, and capture hardware it designs and manufactures. An in-house lab turns the footage into structured data covering motion tracking, 3D reconstruction, and sensor alignment. Mecka claims hand-pose tracking accurate to within a centimetre of data recorded outside the lab. The approach breaks with teleoperation, where people remotely control a robot to generate data. Mecka also works as a robot integrator: it installs hardware, captures data on site, retrains models on it, and runs the system afterwards. The company says it supplies several leading robotics labs and multiple Magnificent Seven companies, the group of the biggest US tech stocks, but it has not named customers. The numbers that need a second look. Mecka says it passed $100 million in run-rate revenue in June, only a few months into operations, and projects $300 million by the end of the year. A run rate annualises recent sales. If the reported $500 million valuation holds, Mecka is priced at about five times its claimed run rate. TechCrunch reports that XDOF, which emerged from stealth on June 17 with a $70 million Series A from Thrive Capital, Spark Capital, Andreessen Horowitz, Lux Capital, and WndrCo, is in late-stage talks for a Series B at about $1.2 billion, led by 8VC, on annualised revenue approaching $50 million. That would be more than 24 times. Forbes reports that Micro1 raised more than $100 million at $4 billion, about eight times the $500 million run rate TechCrunch reported for it in August. The metrics differ and none of the three valuations is confirmed, so treat the comparison as a rough guide. Whether that lower multiple is a bargain or a warning depends on something the numbers cannot show: whether data recorded from human bodies teaches robots as well as data recorded from robots themselves. XDOF collects both, pairing remote robot operation with human collectors who wear sensors. A crowded race for physical AI data. Others are chasing the same shortage from different angles. Encord, which raised a $60 million Series C led by Wellington Management, sells software to manage and label such data rather than collect it. It has raised $110 million in total and said revenue from physical AI customers grew tenfold in the previous 12 months. Micro1 started as an AI recruiting tool, and its founder, Ali Ansari, said on X that it now pays $50 to $90 an hour for people to annotate videos of robots at work, Forbes reported. The capital behind the race is large. Humanoid robot startups raised $8.6 billion by late July, 1.8 times all of 2025, according to Dealroom data cited in aTech Funding News ranking of the top 10 humanoid startups. NVIDIA, which also backed NEURA Robotics' $1.4 billion Series C in June, has now backed both a robot maker and a data supplier. Sequoia already backs Physical Intelligence, a startup that builds AI models for robots and,TFN reported in March, was in talks to raise $1 billion at an $11 billion valuation. Mecka says the money will go to scaling its data infrastructure, deepening its research lab, and expanding commercial robot deployments. It is hiring in research, hardware, and operations. It had about 40 employees in June, according to Fortune, and has not published a hiring target. The test for Mecka is the one its announcement leaves open. It has to show that data recorded from humans measurably improves robots, and that customers it has not yet named will keep paying for it. Until it does, the $100 million run rate is a claim to watch, not a figure to build on.
Mecka announces $60M Series B for robotics AI data. Last Updated: 8 October 2026 Co-founder of JustAINews Key Points * Mecka develops robotics training data from human movements and helps businesses deploy robots in real commercial environments. * Mecka raised $60 million led by Sequoia, with NVIDIA, M12, Qualcomm Ventures, Samsung, Kindred, Framework Ventures, and Neo. * Mecka reported a $100 million annualized revenue run rate in June 2026 and targets $300 million by year-end. Credits: Sequoia Capital What Is Mecka? Mecka is a robotics AI company founded in 2024 that develops data infrastructure and deployment solutions for physical AI. It records human movements and interactions using specialized sensors, then converts that information into datasets that help robots learn real-world tasks. Its services include data collection, AI model evaluation, robot integration, and commercial deployment. Mecka serves robotics research laboratories, AI model developers, and enterprises adopting robotic systems. The company operates data collection programs worldwide and offers EgoVerse, a platform for accessing and analyzing human activity datasets. Mecka's founding team includes Josh Gao, Mogen Cheng, Jason Chong, and Duy Nguyen. Gao and Cheng previously worked together on a financial technology startup serving restaurants, while Chong founded a cryptocurrency exchange that was later acquired by Coinbase. Mecka's $60 Million Series B Funding Mecka raised $60 million in Series B funding led by Sequoia Capital, with new investors including NVIDIA, M12 (Microsoft's Venture Fund), Qualcomm Ventures, and Samsung. Existing backers Kindred, Framework Ventures, and Neo also participated. The company reported exceeding a $100 million annualized revenue run rate in June 2026, within a few months of beginning operations. It expects that figure to reach $300 million by the end of the year. A revenue run rate estimates annual revenue based on a shorter period of business activity, rather than revenue already earned over a full year. Why Robots Need Data From Human Movements AI systems learn by studying examples. Language models can use large collections of written material, while robots need information about movements, physical contact, pressure, and the position of objects. Much of that information needs to be recorded directly from the physical world. Consider a robot learning to fold clothes. It needs to understand where to place its hands, how firmly to hold the fabric, and how to adjust its movements as the material changes position. These details are difficult to capture through ordinary text or video alone. Handling objects accurately remains a challenge in robotics. Humanoid robots still face difficulties with precise movements, flexibility, and independent decisions. Researchers are developing datasets that capture touch and movement information to help machines interact with objects more effectively. These systems have potential uses in manufacturing, warehouses, hospitals, and homes. Better training methods could help businesses introduce robots into workplaces where tasks vary and machines must respond to changing conditions. How Mecka Plans to Use Its $60M Funding Part of the investment will support additional recording equipment. Mecka designs and manufactures its own devices, which contain multiple sensors that capture different aspects of human activity. Its recording teams operate in homes and commercial environments, collecting examples of people performing physical tasks. Research is another priority. Mecka develops computer vision systems, which help computers interpret visual information, and AI models that combine information from several sensors. The resulting data includes hand movements, three-dimensional positions, and measurements that help describe how people interact with objects. According to the company, its technology can track hand positions with accuracy better than one centimeter in real-world conditions. This information is used to prepare datasets for robotics researchers and developers. Mecka also plans to expand its work with commercial customers. It provides robotic equipment, collects data at customer sites, adapts AI models to specific tasks, and handles installation and ongoing operations. The company continues collecting data after robots are deployed, allowing their models to be trained further using information from the workplace. How Mecka's Robot Training Technology Works Mecka's technology covers three main activities. First, its sensors record human movements. AI software then processes those recordings, identifying details such as hand positions and how objects move in three-dimensional space. Finally, quality control systems prepare the information for use in robot training. The aim is to turn everyday human actions into data that robots can learn from. For example, researchers can use recordings of someone handling an object to train a robot to perform a similar task. Mecka has also worked with researchers from Georgia Tech, Stanford, UC San Diego, ETH Zürich, MIT, and Meta through EgoVerse, a study investigating how robots can learn from human demonstrations. The experiments involved different laboratories, robotic systems, and tasks. The company says it supplies several robotics research laboratories and multiple companies belonging to the Magnificent Seven group of major technology businesses. Investors Behind Mecka's Series B The funding also attracted several individual investors, including Tony Xu, founder and CEO of DoorDash; Frank Slootman, former CEO of ServiceNow and Snowflake; and Milan Kovac, who previously led Tesla's Optimus humanoid robotics program. Mecka had secured financing earlier in the year. In June 2026, the company announced a separate $60 million funding round led by Framework Ventures, with participation from Menlo Ventures, SV Angel, and Kindred Ventures. The latest financing will allow Mecka to produce more training data, continue its research, and increase the number of robots deployed in commercial environments. Funding details. * Company name: Mecka * Funding round: Series B * Date: October 2026 * Funding amount: $60 million * Lead investors: Sequoia Capital Get the industry's biggest AI news straight to your inbox.
Mecka AI reveals $60-million USD Series B round backed by Sequoia, Nvidia. Startup aims to provide the real-world training data required to deploy robots. Toronto- and New York City-based Mecka AI has raised a $60-million USD ($86-million CAD) Series B round led by Silicon Valley's Sequoia Capital. Mecka announced the financing on Wednesday. It was supported by new backers like chip giant Nvidia, the corporate venture capital arms of Microsoft and Qualcomm, Samsung, and existing investors Kindred Ventures, Framework Ventures, and Neo. DoorDash co-founder and CEO Tony Xu, ex-ServiceNow and Snowflake CEO Frank Slootman, and the former head of Tesla Optimus Milan Kovac also participated. Mecka aims to build "the data and deployment layer" for physical AI by providing real-world data to train robots. The two-year-old startup also claimed it surpassed a $100-million USD run-rate in June and expects to hit $300 million by the end of this year. Mecka aims to build "the data and deployment layer" for physical AI, providing real-world data sourced from body sensors and iPhones to train humanoids and other types of robots. Demand for this type of data - which, unlike the text, images, and video required to train large language models, cannot be scraped from the internet - is booming. Mecka said this capital will help the company scale its data infrastructure, deepen its internal research lab, and build out its commercial robot deployment layer. TechCrunch first reported last month that Mecka was raising a new Sequoia-led round at a valuation of about $500 million. The new funding comes months after Mecka acquired small, bootstrapped Vancouver-based startup Docula and announced $60 million USD in Series A financing. Mecka secured that amount across an initial, $25-million USD Series A round from last November and a $35-million extension that closed over the summer, financed by Framework, Menlo Ventures, SV Angel, Kindred, and others. Mecka is betting that video captured from a first-person human perspective will help robots learn faster and scale more efficiently. The company collects this data from home settings, culinary work, chemistry labs, task platforms, metal fabrication, and leather shops, and converts it into training-ready data for multiple frontier robotics labs and Big Tech firms. The startup has built hardware replete with sensors to capture this data and the computer vision and multimodal models to turn it into usable training fodder for robots. While Mecka is domiciled in the US, three of its four co-founders are Canadian, and the vast majority of its staff are in Toronto. AI claimed nearly half of all venture dollars invested in Canada last year, and global interest in robotics, humanoid makers, and firms building embodied AI is heating up. The Canadian Robotics Council has clocked "a rapid increase" in the number of robotics startups being launched, both at home and abroad. Vancouver's A&K Robotics and NorBot, Winnipeg's TetraGen Robotics, and Montréal-based Mecademic are among the other startups that have benefitted from this surge. UPDATE (10/07/26): This story has been updated to include additional information shared by Mecka AI. Feature image courtesy Mecka.
Mecka has raised a $60 million Series B led by Sequoia Capital to build an internet-scale dataset for training robots. The New York and Toronto startup also added NVIDIA, Microsoft's M12, Qualcomm Ventures and Samsung as backers. The round brings Mecka's total disclosed funding to $128 million across three rounds since August 2025. The company reported an annual run-rate revenue exceeding $100 million as of June 2026 and expects to reach $300 million by year end. Mecka collects egocentric data by recording human motion from a first-person perspective using body sensors, smartphones and specialised hardware. Participants perform demonstrations of everyday activities in real-world settings. The resulting dataset, called EgoVerse, targets developers working on humanoid robots and embodied AI. The startup employs between 40 and 60 people.