Research Intern: Robot Learning & Embodied AI

Trace; New York (NY); On-site; USD 41,000 - 76,000; Full time

Job summary

Trace is seeking highly motivated Research Interns to join our Brooklyn-based team and tackle challenges at the intersection of robot learning, embodied AI, and human demonstrations. You will own a focused project, collaborating with scientists and engineers to craft methods, run experiments, and evaluate results on real-world data and simulators.

Ideal candidates are pursuing PhD or Master’s studies, with strong ML and robotics foundations, proficient in Python and DL frameworks like PyTorch or

Qualifications

• Currently pursuing a PhD or Master's in Robotics, ML, CS, CS/EE, or a closely related field.
• Publications at leading venues or equivalent research excellence is highly valued.
• Strong programming in Python with experience in modern DL frameworks (PyTorch/JAX); CUDA a plus.

Responsibilities

• Lead an original research project from problem formulation to evaluation with guidance from Trace's team.
• Develop and evaluate novel robot learning methods using multimodal data and real-world datasets.
• Design rigorous experiments and benchmarks to study data quality, transfer, and generalization.
• Work with egocentric video, human demonstrations, and tactile signals as data modalities.
• Collaborate with scientists and engineers to build reproducible pipelines and validate results in simulation or on robots.
• Communicate findings through technical discussions, presentations, and written reports.
• Contribute to high-quality research publications and open artifacts.

Skills

Python programming

CUDA

PyTorch

Research communication

Team collaboration

Education

PhD or Master's in Robotics/ML/CS/EE/ME

Tools

PyTorch

JAX

Job description

Trace is seeking highly motivated Research Interns to join our Brooklyn-based team and tackle challenges at the intersection of robot learning, embodied AI, and human demonstrations. You will own a focused project, collaborating with scientists and engineers to craft methods, run experiments, and evaluate results on real-world data and simulators.

Ideal candidates are pursuing PhD or Master’s studies, with strong ML and robotics foundations, proficient in Python and DL frameworks like PyTorch or