{"id":1672634,"url":"https://alion.io/job/mecka-research-scientist-neural-3d-objects","title":"Research Scientist – Neural 3D Objects","company":{"id":678757,"name":"Mecka","domain":"mecka.ai","url":"https://alion.io/company/mecka","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":95,"open_postings":14,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":109,"computed_at":"2026-10-13T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Toronto, Canada","New York, United States"],"countries":["CA","US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":200000,"max":230000,"currency":"CAD","period":"year","gross":null,"usd_annual":161145},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Embodied AI","optional":false},{"name":"Gaussian Splatting","optional":false},{"name":"NeRF","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Open3D","optional":true}],"status":"live","first_seen_at":"2026-10-01T19:33:48Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-14T02:13:06Z","board_verified":true,"closed_at":null,"days_open":12,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":12},"description":"About Mecka AI\nMecka AI is building the data infrastructure layer for robotics and embodied AI.\nWe 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.\nWe work closely with frontier robotics teams to bridge real-world data, simulation, learning-based systems, and deployed hardware.\nThe role\nWe're looking for a neural objects researcher to own the architecture for generating 3D objects from video. Given egocentric footage of someone manipulating an object, you build the models that recover its geometry - and, ultimately, a simulatable asset with the physical properties to drop into a physics simulator.\nYou'll own the hardest, most open part of the objects effort: reconstructing objects that are small in frame, partly occluded by the hand, and sometimes deformable. You'll push the frontier, then hand results to the integrations researcher who takes them into the production pipeline.\nThis is a research role for someone who wants an open, unsolved problem on real, large-scale data - not a fully-specified spec.\nWhat you'll do\nNeural 3D reconstruction. Models that recover object geometry from monocular / egocentric video - sequential and multi-view approaches robust to occlusion and low resolution.\n\nGenerative refinement. Use generative 3D to complete and clean up partial reconstructions while rejecting hallucinated geometry.\n\nToward simulatable objects. Move beyond geometry toward assets that carry physical properties and rigging, so a reconstructed object can be simulated, not just rendered.\n\nContact-aware reconstruction. Use hand contact as a signal to constrain object shape and pose where the hand touches the object.\n\nDeformables. Take on the genuinely hard frontier - objects that change shape as they're handled.\n\nPrototype & hand off. Build research prototypes and hand them to the integrations researcher for productization; publish where it makes sense.\n\nWhat we're looking for\nStrong 3D / neural-reconstruction research. Neural implicit or explicit 3D, 4D reconstruction, or generative 3D - you've worked at this frontier.\n\nDeep-learning depth. You design and train models, and can read and reproduce frontier papers.\n\n3D geometry foundation. Structure-from-motion / multi-view geometry, meshes, and differentiable rendering.\n\nResearch taste. You can find the tractable decomposition of a hard, open problem and make steady progress on it.\n\nEngineering to match. You prototype fast in clean Python / PyTorch and can get a research idea working on real data.\n\nStrong plus\nGenerative 3D (diffusion / feed-forward 3D-generation families).\n\nDifferentiable rendering, NeRF, or Gaussian splatting.\n\n4D / dynamic-scene reconstruction from video.\n\nPhysics simulation and rigging - turning geometry into a simulatable asset.\n\nHand-object interaction; publications at top vision or graphics venues.\n\nTech stack\nPython / PyTorch (primary) for model design and training.\n\n3D deep learning - neural implicit / explicit representations, differentiable rendering.\n\nGenerative-3D toolkits; mesh processing (Open3D, trimesh).\n\nPhysics simulators for the path from geometry to simulatable object.\n\nThe exact stack matters less than depth in 3D deep learning and the judgment to make progress on an open problem.\nHow this role fits - you own neural 3D object generation: reconstructing manipulated objects from monocular egocentric video, including the hard cases - heavy occlusion, low resolution, and deformable objects - and pushing toward objects that carry the physical properties needed to be simulated. This is an architecture-level research role that sets the direction the objects team builds on.\nWhat success looks like\nManipulated objects reconstruct from egocentric video at usable quality - including small, occluded, and deformable cases.\n\nA credible path exists from interaction video to a simulatable 3D object.\n\nYour research transfers into the pipeline through the integrations seat, not just into papers.\n\nThe objects pod builds on the architecture and direction you set.\n\nWho this role is not for\nApplied-only engineers who don't want open-ended research.\n\nResearchers who need a fully-specified problem handed to them.\n\nAnyone without a 3D and deep-learning foundation.\n\nWhy this role at Mecka\nDefine how a company turns everyday manipulated objects into simulatable 3D assets.\n\nOwn an open, high-impact research problem on real, large-scale egocentric data.\n\nA clear path from research to product through a dedicated integrations seat.\n\nDirect impact on the data that trains real robots.\n\nA Note on Applying\nStudies 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.\nInclusive Hiring at Mecka\nWe 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.\nUse of Artificial Intelligence in Recruitment\nMecka 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. 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