• Develop and Deploy Models: Design, develop, and implement machine learning models for high-performance recommendation systems and personalized feeds. Candidates without direct experience in recommendations and ranking are still encouraged to apply if they possess exceptional technical skills in other areas of machine learning.
• Large Language Model Expertise: Leverage large language models (LLMs) to create scalable, intelligent solutions for content understanding, user engagement, and relevance ranking.
• Experimentation and Analysis: Drive data-driven experimentation using A/B testing, advanced analytics, and statistical techniques to identify growth opportunities and refine algorithms.
• Infrastructure Optimization: Develop and optimize pipelines, tools, and infrastructure to support real-time decision-making, personalization, and predictive analytics.
• Technical Leadership: Mentor team members and foster collaboration within cross-functional teams, including engineers, product managers, and designers.
• Continuous Innovation: Stay informed on emerging trends in AI and machine learning, and integrate them to drive innovation and improve product offerings.
• Cross-functional Collaboration: Articulate findings and recommendations to technical and non-technical audiences, influencing decisions across teams and leadership.
• Embody our Culture and Values.

Required Qualifications

• Bachelor's Degree in Computer Science, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Preferred Qualifications

• 3+ years of experience building and deploying ML models in production environments.
• Strong coding skills in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow).
• Familiarity with data processing tools (e.g., Spark, Pandas) and cloud platforms (e.g., Azure, AWS).
• Experience with classification, recommendation, or personalization systems.
• Experience using large language models (LLMs) for machine learning and AI applications.
• Hands-on experience in growth engineering, driving improvements in user acquisition, engagement, and retention.
• Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Expertise in personalization strategies and user behavior modeling.
• Strong problem-solving skills and the ability to independently design solutions to complex challenges.
• Excellent communication skills, with the ability to influence technical and non-technical audiences.
• Ability to work in a fast-paced environment, manage multiple priorities, and adapt to changing requirements and deadlines.

Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $158,400 - $258,000 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

Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 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 $188,000 - $304,200 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

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.