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1 month ago
Our Mission Our mission is to solve the most important and fundamental challenges in AI and Robotics to enable future generations of intelligent machines that will help us all live better lives. Foundation Model Research Scientists will have proven hands-on research or industry experience focusing on one or more of these key areas: Cognitive AI, Foundation Models, Large Language Models, and Distributed Training. If you are passionate about developing technology for robots and using it to advance their capabilities and usefulness, this team will be a great fit for you Responsibilities Develop deep learning-based approaches to improve and advance large language models (LLMs) and large multi-modal models. Design and implement machine learning techniques to adapt foundation models to downstream tasks of interest such as robotic manipulation and high-level task planning. Construct and curate datasets for large-scale machine learning, for learning from human preferences, and for specific domains of applications. Work closely with our research teams to build state-of-the-art robotics demonstrations of your research. Requirements MS or PhD in a foundation-model-relevant field 7+ years of experience in research and development Knowledge of large language models, foundation models, model parallelism, or distributed training techniques. Excellent programming skills in some rapid prototyping environments such as Python or C++ Expertise with deep learning frameworks such as PyTorch. 1 or more publications in top-tier conferences and journals in Machine Learning, Robotics, or related fields (e.g. CVPR, ICCV, ECCV, TPAMI, IJCV, NIPS, ICLR, ICML, IJRR, ICRA, IROS, RSS, ACC, CDC, etc.) Bonus Experience with Docker, Kubernetes, cloud computing, or similar applications Experience with data processing, logging, and visualization tools Experience with MLOps (model versioning, model and data lineage, monitoring, model hosting and deployment, scalability, orchestration, continuous learning) Experience creating orchestration workflows with tools such as Airflow, Kubeflow, or AWS Step Functions Experience with DevOps tools (e.g. CI/CD Pipelines, Infrastructure as Code, containers, Agile software development) Experience implementing IoT solutions such as edge computing Experience with big data batch and real time data processing (e.g. Hadoop, Spark , Presto, Kafka, Kinesis, Flink) Proven track record of publications in top-tier conferences and journals in Machine Learning, Robotics, or related fields (e.g. CVPR, ICCV, ECCV, TPAMI, IJCV, NIPS, ICLR, ICML, IJRR, ICRA, IROS, RSS, ACC, CDC, etc.) Experience with parallel programming (e.g. CUDA) These attributes are great to have but not required for our candidates. Candidates who lack these should not be discouraged from applying. We provide equal employment opportunities to all employees and applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. #J-18808-Ljbffr
