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Research Scientist, Multimodal Alignment, Safety and Fairness, DeepMind

Google
Kirkland, USA
Mid
Onsite
USD 147000-210000 / year
Discovered 2 days ago
jaxpython

Full Job Posting

Responsibilities

  • Generate new ideas, keep up with the state-of-the-art in the field, and discuss research directions with other researchers.
  • Design, rapidly implement, and evaluate ideas, methods, interfaces, and tools to explore new sociotechnical AI systems.
  • Report and present research findings and developments clearly and efficiently both internally and externally, verbally and in writing.
  • Suggest and engage in inter and intra-team collaborations to meet ambitious research goals, while also driving significant individual contributions.
  • Take ownership of substantial technical projects, from ideation and design to implementation and evaluation, often involving cross-functional collaboration.

Minimum qualifications:

  • PhD degree in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
  • Experience in Python and deep learning frameworks (e.g., JAX, Flax, or Gemma).
  • Experience in developing multimodal AI models and systems.
  • Experience conducting research and development, including experimental design, implementation, and analysis.
  • Publication record in machine learning conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, ECCV).

Preferred qualifications:

  • Experience fine-tuning and post-training LLMs using Reinforcement Learning (RL) or other alignment methods.
  • Experience with developing generative AI architectures, techniques, and agentic AI solutions.
  • Experience with multimodal learning, integrating information from different data types (e.g., vision, audio, text).
  • Proven expertise in working with, tuning, and prototyping large-scale vision-language models (VLMs) using modern prompting strategies.
  • Strong interest in and awareness of the AI alignment, safety, responsibility, and fairness landscape, with an excitement to collaborate across disciplines.

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