Applied Scientist - Gaming
Redmond, Washington, United States
Full Time Mid-level / Intermediate USD 98K - 208K
Microsoft
Entdecken Sie Microsoft-Produkte und -Dienste für Ihr Zuhause oder Ihr Unternehmen. Microsoft 365, Copilot, Teams, Xbox, Windows, Azure, Surface und mehr kaufenXbox Game Studios makes some of the best AAA games on the planet and the opportunities for a motivated Applied Scientist are endless. You will have the chance to work on AI/ML projects and deliver solutions that will change the way we develop games and entertainment services.
We are an agile team within Xbox Games Studios Quality tackling a wide range of problems throughout the game development process.
As an Applied Sciences Specialist in Xbox Games Studios Quality, you will be working with major franchises that include Halo, Forza, Gears of War and Microsoft Casual Suite. You will also be involved in all phases of development and sustainment efforts. This opportunity will allow you to research and deploy deep learning solutions in computer vision and reinforcement learning. You will have the opportunity to bring SOTA solutions to the game development pipeline. This position includes flexible work from home options.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
- You will gain expertise in one or more subareas of research and understand applicable research techniques. You’ll also gain deep knowledge of a service, platform, or domain, and become familiar with the latest industry trends and applied technologies.
- You will apply strategies provided by senior team members and incorporate state-of-the-art research. You’ll also develop an understanding of methods used in the community and gain expertise in a deeply specialized area.
- As you reinforce a positive environment by applying best practices, you will also support mentorship and assist with the onboarding of entry-level team members. Additionally, you will maintain ties with an external network of peers and identify prospective talent, when asked.
- You will document work in progress and share findings to promote innovation within a group. You’ll also learn and follow ethics and privacy policies while executing research processes or collecting information.
- You will research and develop an understanding of tools, technologies, and methods being used in the community that can be utilized to improve product quality, performance, or efficiency. Apply deep subject matter expert knowledge around several specialized tools/methods to support business impact.
Qualifications
Required/Minimum Qualifications (RQs/MQs)
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research)
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
- OR equivalent experience.
- 2+ years experience in implementing and evaluating deep learning models using established frameworks such as Pytorch, JAX, or Tensorflow.
- 2+ years experience in 3D computer vision (e.g., segmentation, scene understanding), vision generative modeling (e.g., latent diffusion models), and/or deep reinforcement learning agents for exploration and control in complex 3D environments.
Additional or Preferred Qualifications (PQs)
- Doctorate in computer science, deep reinforcement learning, imitation learning, robotics, or control AND 1+ years related experience
- OR equivalent experience
- 1+ year(s) experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
- 2+ years experience in researching and applying deep reinforcement learning agents or 3D generative modeling in simulated 3D environments.
Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $98,300 - $193,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $127,200 - $208,800 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
Microsoft will accept applications for the role until March 11, 2025
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
#studiosquality
Tags: Agile Computer Science Computer Vision Deep Learning Diffusion models Econometrics Engineering Generative modeling JAX Machine Learning Privacy PyTorch Reinforcement Learning Research Robotics Statistics TensorFlow
Perks/benefits: Career development Equity / stock options Flex hours Medical leave
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