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.

About Mecka AI

Mecka AI is building the data infrastructure layer for robotics and embodied AI.

We partner with leading AI labs and robotics companies to deliver high-quality, real-world datasets used to train, evaluate, and deploy robotic systems. Our work sits directly between research, data, and real-world execution — where model performance is dictated by data quality.

Our Mission

Robotics will become the largest industry in human history — larger than anything that has come before it. As intelligent machines move into the physical world, they will dramatically expand global GDP, raise the material standard of living for everyone, and ultimately help make humanity a multiplanetary civilization. None of that happens without one thing: enormous amounts of high-quality, real-world data.

Mecka AI builds that foundation. We are the data infrastructure layer for robotics and embodied AI — the substrate that teaches machines to perceive, reason, and act in reality. Get this right, and we accelerate the most important technological transition of our time.

Our Culture

• Excellence as the baseline. We hold an extremely high bar and expect the best work of your career. Mediocrity isn't interesting to us.

• Highly technical. We reason from first principles, not by analogy. The best argument wins — regardless of title or tenure.

• Truth-seeking. We are relentlessly honest with ourselves and each other. We chase reality — measured, not assumed — and kill our own bad ideas fast.

• Maniacal urgency. The work matters and the clock is real. We move fast, ship, measure, and iterate.

• Extreme ownership. You own outcomes end-to-end — no hand-offs, no excuses, no waiting for permission.

• Hardcore. This is a high-intensity environment for people who want to do the defining work of their lives.

The Role

We are looking for a Research Scientist, Video Understanding to own Mecka’s video understanding agenda end-to-end: train large-scale video representation and video-language models on our egocentric + stereo corpus, and turn the resulting checkpoints into production signals the rest of the stack ships on.

This role is focused on large model training, video encoders, video-language models, VLMs/VLAs, and temporal representation learning on real-world robotics data.

What You’ll Work On

Large-Scale Training & Architecture

• Own model architecture and training strategy across Mecka’s task families (manipulation, locomotion, daily activity, long-horizon behavior).

• Run self-supervised and multimodal pretraining (VideoMAE / VJEPA / VideoPrism / InternVideo-class) with rigorous evals and clean ablations.

Video-Language & Multimodal Modeling

• Train and fine-tune video encoders and video-language models (temporal transformers, joint-embedding models, contrastive objectives, masked modeling, instruction/video alignment).

• Incorporate useful priors (pose, depth, camera motion, optical flow) when it improves representation quality.

Research → Production Signals

• Turn checkpoints into usable artifacts: embeddings and model outputs that downstream systems can reliably consume (retrieval, labeling, QA, analytics).

• Build a disciplined training + eval workflow with regression tracking and reproducible runs.

Who You Are

Required Background

• Deep experience training large models in PyTorch (or equivalent), including multi-GPU or distributed training.

• Strong understanding of modern video representation learning and/or multimodal modeling.

• Ability to run rigorous experiments and communicate results clearly.

• Warning: Research Scientist positions require hyper-specific expertise. Please limit your applications to one research role. Applying to multiple Research Scientist positions suggests a lack of focus and may result in the rejection of all submissions. You may, however, apply to other non-research roles alongside your research application.

Strong Signals:

• Experience with video VLMs / VLA-adjacent systems (VideoCLIP, InstructBLIP-Video, LLaVA-Video-class).

• Experience with egocentric / embodied datasets (Ego4D, EgoExo4D, EPIC-Kitchens, Something-Something).

• Strong software engineering discipline: you write research code that can be shipped.

Why This Role

• Work on a domain — egocentric embodied video — where data is scarce everywhere except here.

• Own a research agenda that directly feeds production systems and product outcomes.

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.