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AI Research Intern- Multimodal Machine Learning

Bosch Group

AI Research Intern- Multimodal Machine Learning

Pittsburgh, PA
  • Responsibilities

    Job Description

    Bosch Research Pittsburgh would like to invite an enthusiastic and knowledgeable machine learning research intern for investigations at the intersection of natural language processing, multimodal representation learning, and sequential decision-making. We wish to develop adaptive intelligent systems, capable of reasoning over various sensor data streams and heterogeneous data sources (e.g., video feeds, textual meta-data, knowledge graphs) in order to satisfy such downstream tasks as video content understanding, visual question-answering, building automation/control, or natural language robot navigation. We expect the intern to implement and evaluate various methods, inspired by both your own insights and by contemporary academic literature. Viable methods include end-to-end neural systems and hierarchical AI methods; regardless of the chosen method(s), the intern must understand the relevant challenges of dataalignment, practical implementation, model generalizability, overall system robustness, and performance characterization. Together with our faculty collaborators in the School of Computer Science and College of Engineering at Carnegie Mellon University (CMU), we have made several key developments that we expect the prospective intern to leverage and extend. Finally, the prospective intern will work with teammates to publish a research paper in a top-tier AI venue. Tasks

    • Perform extensive literature review, to understand the current state-of-the art
    • Generate a research plan, detailing intended approaches and evaluation methods
    • Present related work and research progress to colleagues, on a weekly basis
    • Develop self-contained reasoning agent and perform exhaustive evaluation
    • Summarize findings as a high-quality research paper
    • Formalize findings as contribution to patent filing (if applicable)
  • Qualifications


    • Strong background in machine learning, deep learning, and natural language processing
    • Extensive experience in from-scratch deep learning model development, using PyTorch
    • Extensive experience in developing in Python on Linux
    • Experience in neural methods for Computer Vision and visual content understanding
    • (Preferred) Experience with data analytics toolkits, such as scikit-learn, MATLAB, or R
    • (Preferred) Mature researcher, with existing publication history in top conference venues,e.g., NIPS, ICML, ICLR, CVPR, ICCV, ACL, NAACL, EMNLP, IJCAI, AAAI, CIKM
    • (Bonus ) Familiarity with W3C Semantic Sensor Network (SSN), SOSA, etc.
    • (Bonus) Familiarity with information retrieval and ontological reasoning


    • Degree Level: doctoral or post-doctoral
    • Major:
      • Computer Science
      • Electrical & Computer Engineering
      • Cognitive Science
      • Statistics
      • (or related)

    Additional Information

    • Location: Pittsburgh, Pennsylvania, United States
    • Start date: Typically, between April and June
    • Duration: Typically, 14 weeks (extension possible; subsequent research collaboration encouraged)

    By choice, we are committed to a diverse workforce - EOE/Protected Veteran/Disabled.

    BOSCH is a proud supporter of STEM (Science, Technology, Engineering & Mathematics) Initiatives

    • FIRST Robotics (For Inspiration and Recognition of Science and Technology)
    • AWIM (A World in Motion)