Senior AI/ML Engineer - PowerPoint
Microsoft
Senior AI/ML Engineer - PowerPoint
Mountain View, California, United States
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Overview
Join the PowerPoint team as we deliver modern, intelligent, and collaborative experiences that will delight millions of PowerPoint customers. Located in the heart of Silicon Valley in Mountain View, CA, we are looking for an experienced machine learning engineer who is excited to apply ML to real-world problems and adapt LLMs to task oriented domain specific using techniques such as finetuning and reinforcement learning that will go into production.
On our team, understanding the customer is just the beginning. We analyze customer data, understand their problems, including finetune models to address these issues, and collaborate with partner teams to deploy these models as customer-facing features. A flexible problem-solving attitude and the ability to collaborate across disciplines are vital. You will be responsible for working within Microsoft’s industry-leading commitments to user privacy and ensuring that your models and features adhere to Microsoft’s Responsible AI policies to ensure fair and unbiased experience for all.
The PowerPoint team boasts mature development and engineering systems. Our engineers benefit from rich telemetry, data-driven decisions, rapid experimentation, and building on a world-class platform. We also have a great management team with extensive experience to help you advance your career. Our products and portfolio are rapidly expanding, and we are excited to meet the challenges of scale, performance, efficiency, and reliability as we build the world's finest storytelling software.
We are looking for Senior AI/ML Engineer to join our team in Mountain View, CA.
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.
Qualifications
Required Qualifications:
- Bachelor's Degree in Computer Science or related technical field 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.
- 4+ years of experience in machine learning, deep learning, natural language processing, computer vision, and/or statistics.
- 4+ years of experience in software development.
Other Requirements:
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Preferred Qualifications:
- Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
- 5+ years of experience in end-to-end development for building, shipping, and iterating on high-impact ML models.
- Proficiency in Python and familiarity with coding in multiple languages.
- Proficiency in using ML libraries from sources such as Hugging Face.
- Expertise in implementing, training, and debugging transformer-based ML models and other related tools and technologies for building and shipping large language models (LLM) applications.
- Deep knowledge of algorithms, machine learning, and distributed/cloud computing systems (e.g., Spark, Hadoop, Azure).
- Contributions to open-source ML projects are a plus.
- Effective communication skills, maintaining customer experience and quality along with the ability to work across groups and disciplines.
- Ability to quickly ramp up on various domains within Machine Learning.
- Experience shipping high-quality products at scale is a plus.
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
Microsoft will accept applications for the role until June 23rd, 2025.
Responsibilities
- Collaborates with appropriate stakeholders to determine user requirements for a scenario.
- Drives identification of dependencies and the development of design documents for a product, application, service, or platform.
- Creates, implements, optimizes, debugs, refactors, and reuses code to establish and improve performance and maintainability, effectiveness, and return on investment (ROI).
- Leverages subject-matter expertise of product features and partners with appropriate stakeholders (e.g., project managers) to drive a workgroup's project plans, release plans, and work items.
- Acts as a Designated Responsible Individual (DRI) and guides other engineers by developing and following the playbook, working on call to monitor system/product/service for degradation, downtime, or interruptions, alerting stakeholders about status and initiates actions to restore system/product/service for simple and complex problems when appropriate.
- Proactively seeks new knowledge and adapts to new trends, technical solutions, and patterns that will improve the availability, reliability, efficiency, observability, and performance of products while also driving consistency in monitoring and operations at scale.