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# AI Researcher

- **Company:** Microsoft
- **Location:** United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Big Data, Continuous Integration, Python (Programming Language), Machine Learning, Network Architecture, Software Engineering, Reinforcement Learning, Pytorch, Large Language Models, Deep Learning, Information Technology, Data Pipelines
- **Published:** September 15, 2026
- **Apply:** https://www.comeet.com/jobs/mentee_robotics/6A.002/ai-researcher/7E.956

## About the Role

* Proven experience (M.S., Ph.D., or equivalent industry experience) in Computer Science, AI, or a related field.
 * Strong software engineering skills are non-negotiable; demonstrated excellence in solving complex engineering problems, particularly in Python.
 * A deep, "under the hood" understanding of modern deep learning, including network architectures, loss functions, optimization, and transformers.
 * Extensive hands-on experience with PyTorch.
 * A proven track record of training large-scale deep learning models on large datasets.
 * Ability to thrive in a fast-paced, high-impact environment where solutions are often unclear and require deep exploration.

Nice to have:

 * Experience with training large models (e.g., LLM, VLM, VLA).
 * Prior experience working with robotic learning systems.
 * Experience with multi-task learning, imitation learning, or reinforcement learning.
 * A strong publication record in top-tier AI or robotics conferences (e.g., NeurIPS, ICML, CVPR, RSS, CoRL).

## Description

* Design, implement, and train state-of-the-art neural network architectures for robotic applications, including large multimodal models (vision, language, sensor data) and generative models.
 * Architect and maintain scalable deep learning frameworks for training on massive, real-world robot datasets.
 * Develop and implement cutting-edge techniques in areas such as imitation learning, reinforcement learning, self-supervised learning, and video-based models.
 * Own the full machine learning lifecycle: define data collection and labeling strategies, build high-throughput data pipelines, and establish robust evaluation and deployment protocols.
 * Collaborate closely with software, hardware, and controls teams to integrate and test your models on physical robots.
 * Leverage and contribute to internal tooling for large-scale data processing, model experimentation, and continuous integration.


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