Research Scientist, Robotics – World Models

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🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $160k - $185k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧬 Research Scientist

👻 Ghost score 20%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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InnoData

WebsiteLinkedInAll Job Openings

2 - 10 employees

Founded 2019

🤝 B2B

💼 Consulting

🌍 Social Impact

B2B • Consulting • Social Impact

InnoData is INNOvation DATA SCS, an Italian social cooperative based in Foggia that identifies itself as a provider of technological solutions. The company website (currently under maintenance) highlights "Soluzioni tecnologiche" (technological solutions) and emphasizes social impact ("Impatto sociale"). Contact details listed include Via Francesco Crispi 65, 71121 Foggia, Italy. Based on the available information, InnoData appears to operate at the intersection of technology and social impact, likely offering tech-focused services to other organizations.

📋 Description

• Define how Innodata designs, structures, and evaluates data for robot foundation models • Translate robotics foundation-model requirements into data specifications, including modalities, action representations, sampling, annotation schemas, and evaluation criteria • Decide what to capture in the real world versus generate in simulation • Curate and weight training mixes across heterogeneous robot datasets, embodiments, action spaces, and sensor setups • Guide data collection across motion-capture, egocentric, exocentric, teleoperation, multi-sensor, and synthetic-data pipelines • Build evaluation and benchmarking methods that predict real-world transfer, including world-model evaluation and sim-to-real methodology • Fine-tune and evaluate foundation models on Innodata data through data-quality ablations and scaling studies • Design adversarial and long-horizon evaluations and convert failure modes into improved data • Publish benchmarks, methodologies, and papers • Collaborate with capture, annotation, and synthetic-data teams to operationalize collection and labeling plans

🎯 Requirements

• Roughly 4+ years of hands-on industry experience in robot learning or robotics ML • Bachelor's degree in computer science, electrical engineering, robotics, or a related technical field is required • Trained and evaluated robot policies using imitation learning or reinforcement learning • Strong PyTorch fundamentals • Experience curating, filtering, and weighting robot data across embodiments and sensors • Fluency in the LeRobot dataset format, RLDS, Open X-Embodiment, and common motion and sensor formats • Hands-on experience with NVIDIA Isaac Sim, Isaac Lab, Omniverse, MuJoCo, or comparable simulation engines • Experience with domain randomization, system identification, and sim-to-real transfer • Experience with teleoperation or egocentric data collection • Experience adapting VLM backbones for control and fine-tuning large VLA models using HuggingFace transformers and PEFT • First-author publications or strong open-source contributions at venues such as CoRL, ICRA, IROS, RSS, or NeurIPS • Ability to work with customer and frontier-lab research scientists and explain data and modeling decisions clearly • Rigorous, reproducible approach to experiments and documentation