AI/ML Engineer

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The Azure Resource Graph team is looking for a AI/ML Engineer. As a AI/ML Engineer you will be building training and inference environments using Azure ML and AKS. You will be building software to power conversational AI experiences using LLMs that can draw inferences from vast datasets, both structured and unstructured, collaborating in agile teams with the goal of building self-learning systems that learn from the ever-changing real-world data. We are looking for a motivated, results-oriented, and collaborative engineer who has a drive for results and a passion for learning.

This role will combine machine learning and AI knowledge with software engineering expertise, while demonstrating a growth mindset and customer empathy. Join us in shaping the future of AI agents.

You will play a crucial role in developing the Azure Resource Graph team’s direction in machine learning, Generative AI model fine-tuning, Agent creation and deployment, AI evaluation and scaling.

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.

• Bachelor's degree in CS/Applied Mathematics/Statistics/DS/ML or related fields
• Experience developing machine learning solutions.
• Experience working with Web Scraping frameworks, Programming Language Grammars, and Parser Generators
• Experience with DevOps frameworks and CI/CD pipelines shipping quality software
• Technical leadership experience in data driven software engineering

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.

• Bachelor's Degree in Computer Science or related technical field AND 1+ 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 with proven experience coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.
• 1+ years of experience in using agents/AI tools including, but not limited to Cline, Roo.
• 1+ years of experience with Visual studio.

Software Engineering IC2 - The typical base pay range for this role across the U.S. is USD $84,200 - $165,200 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 $109,000 - $180,400 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 October 23, 2025.

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• Perform software development in Python, C#, C++ as needed to build LLM training, testing, and inference modules
• Supports identification of dependencies, and the development of design documents for a product feature with oversight.
• Leads the creation and implementation of innovative AI software using traditional ML, NLP, and statistical learning approaches
• Able to break down work items into tasks, provides estimation, and manage ambiguous requirements.
• Reviews current developments and proactively seeks new knowledge that will improve the availability, reliability, efficiency, observability, and performance of products while also driving consistency in monitoring and operations at scale.
• Apply best practices, coding standards and patterns.
• Develop a deep understanding of the Azure Resource Graph and Azure best practices.