Senior Applied Scientist (bing Places)

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Applied Sciences

Senior Applied Scientist role focused on leveraging LLMs, SLMs, and RAG models to improve the Bing Places platform. The role involves designing, developing, and deploying AI solutions, creating data pipelines, and staying updated on AI/ML research. Collaboration with multidisciplinary teams and mentoring junior members are key aspects.

What you'd actually do

  1. Develop and deploy solutions leveraging LLMs, SLMs, and RAG models to solve complex data challenges and enhance the Bing Places platform.
  2. Stay informed about the latest advancements in AI/ML research, evaluate their applicability, and integrate them into scalable systems.
  3. Collaborate across multidisciplinary teams, including engineers, data scientists, and product managers, to translate research insights into actionable solutions.
  4. Create robust pipelines for data processing, training, and inferencing to optimize model performance and scalability.
  5. Mentor junior team members, foster knowledge sharing, and support recruiting efforts to build a world-class research team.

Skills

Required

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience
  • Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience
  • Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience
  • equivalent experience

Nice to have

  • Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience
  • Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience
  • equivalent experience
  • 3+ years of experience in publishing peer-reviewed research or presenting at conferences.
  • Proven expertise in developing and deploying AI solutions in production environments.
  • Experience working with cloud-based infrastructure and big data technologies.

What the JD emphasized

  • production environments
  • scalable systems

Other signals

  • LLMs
  • SLMs
  • RAG
  • production environments
  • scalable systems