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Data & Applied Scientist

Data Science Jobs ⫽ Data Scientist

Cambridge

Competitive salary

Permanent, Full time

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Job description

Would you like to be at the forefront of AI and Gaming and work with state-of-the-art AI research and the top gaming studios in the world? At Gaming AI, we are exploring emerging technology trends to craft the next era of gaming. We are venturing beyond the horizon and charting a course forward with players and creators at the center. Our goal is to define the future of Xbox by advancing our mission of bringing joy and community to every player on the planet. If you value dynamic and agile teams that are proactively advocating for a diverse workforce, we have a great role for you.

We are seeking an applied scientist/machine learning engineer with excellent problem-solving skills and a passion to apply advanced AI techniques in gaming domains. As a key contributor, you will develop state-of-the-art machine learning techniques to elevate user and content experience to the next level in gaming. You will collaborate with a diverse global team of engineers and data scientists that develops and applies sophisticated machine learning techniques (e.g., reinforcement learning, computer vision, natural language processing, recommender systems and more) in gaming related products.

Responsibilities

In this role, you will collaborate with experts in machine learning and distributed systems. You will get to work on reinforcement learning, computer vision, LLMs and other advanced machine learning techniques. Your ML models will help advance the state of the art in both production and distribution of the gaming industry. You will work on all aspects of the design, development and delivery of machine learning and deep learning solutions, including problem definition, data acquisition, exploration, training, testing, and evaluating machine learning models, and creating end-to-end data pipelines and solutions in production.

Qualifications

Qualifications:

  • MS in CS/EE/Applied Mathematics/Statistics/DS/ML or related fields.
  • Experience developing machine learning solutions.
  • Proficiency in Python.
  • Strong intellectual curiosity and learning capacity
  • Effective problem-solving acumen and critical thinking skills.
  • Ability to thrive in a dynamic, fast-paced work environment.

Preferred Qualifications:

  • Experience in machine learning engineering and/or AI research.
  • Proficiency in one statically typed language (C#, Java, C, C++).
  • Familiarity with software engineering principles and best practices.
  • Experience deploying and managing machine learning models and data pipelines.
  • Experience working with real-world noisy data.
  • Outstanding communication and collaboration skills.
  • Experience in videogame development or previous exposure to the gaming industry.
  • Visionary Thinking: Demonstrate a proven ability to think beyond the immediate scope, envisioning future possibilities and trends within the ever-evolving landscape of technology and incubation products.
  • Comfort with Ambiguity: Thrive in an environment characterized by uncertainty and ambiguity. Possess the adaptability and resilience to navigate uncharted territories, embracing the challenges of operating in the unknown.

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. 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.

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