Member of Technical Staff, Machine Learning Engineer

Overview:

As Microsoft continues to push the boundaries of AI, we are on the lookout for passionate individuals to work with us on the most interesting and challenging AI questions of our time. Our vision is bold and broad - to build systems that have true artificial intelligence across agents, applications, services, and infrastructure. It's also inclusive: we aim to make AI accessible to all - consumers, businesses, developers - so that everyone can realize its benefits.

Microsoft AI (MAI) is looking for a talented and experienced Machine Learning Engineer to join our Growth team and help shape the next generation of AI systems, specifically for our personal AI assistant, Copilot. This role focuses on optimizing user engagement, retention, and personalization with innovative AI solutions, with a strong preference for expertise in recommendation systems and feed algorithms. However, we also welcome candidates with broader machine learning experience and a passion for solving dynamic AI challenges.

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.

By applying to this Mountain View, CA position, you are required to be local to San Francisco area and in office 3 days a week.

Responsibilities:

• 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.

Qualifications:

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.
• Proficiency in programming languages like Python or R, with experience in data processing frameworks (e.g., Spark, Hadoop).
• Demonstrated success in working with large datasets and cloud platforms such as AWS, Google Cloud Platform, or Azure.

Preferred Qualifications:

• Advanced degree (PhD/MS) in Computer Science, Machine Learning, AI, or a related field; or equivalent experience.
• Proven expertise in building and deploying recommendation systems and personalized feed algorithms at scale.
• 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.

Machine Learning Engineer IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 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 $153,600 - $250,200 per year.

Machine Learning Engineer IC5 - The typical base pay range for this role across the U.S. is USD $137,600 - $267,000 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 $180,400 - $294,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft will accept applications and processes offers for these roles on an ongoing basis.

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