Machine Learning Engineer II

Microsoft is a company where passionate innovators come to collaborate, envision what can be and take their careers further. This is a world of more possibilities, more innovation, more openness, and the sky is the limit thinking in a cloud-enabled world.

The AI Platform organization at Microsoft builds the end-to-end Azure AI stack/PaaS and is core to Azure’s innovation and differentiation, as well as all of Microsoft’s flagship products, from Office to Teams, to Xbox. We are the team building Azure OpenAI, Azure ML, Cognitive Services, and the global Azure AI infrastructure for running the largest AI workloads on the planet.

We do not just value differences or different perspectives. We seek them out and invite them in so we can tap into the collective power of everyone in the company. As a result, our customers are better served.

 Within AI Platform, the AI Services team empowers developers and data scientists around the world and of all skill levels to easily add AI capabilities to their apps.

We are looking for a Machine Learning Engineer II to join our team.This role requires a deep understanding of generative AI use cases and responsible AI, a keen sense of model development to support responsible AI commitments while keeping product innovation in mind, and a technical background to develop responsible AI measurement and mitigation techniques.

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.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Required Qualifications:

• Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

                     o OR equivalent experience.

• 2+ years experience in machine learning, deep learning and/or related fields.
• 2+ year experience in software development experience in languages such as Python, Java, C++, Scala, or C#
• 2+ year experience developing end to end ML (Machine Learning)/DL (Deep Learning) engineering systems.
• 2+ year experience in distributed/cloud computing systems (e.g. Spark, Hadoop, Azure, AWS, Cosmos).

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:

• Have research or work experience on NLP, or recommendation system.
• Experience working in the Gen AI field.
• Experience developing and designing science model consumed in production development.
• Experience working through full product cycles from initial design to final product delivery.
• Knowledge and experience in large scale data analytics, such as Spark. 

Software Engineering IC3 - The typical base pay range for this role across the U.S. is USD $98,300 - $193,200 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 $127,200 - $208,800 per year.

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

Microsoft will accept applications for the role until January 6, 2025. 

#aiplatform

We are seeking an enthusiastic AI engineer who is passionate about the latest AI advancements, possesses a start-up mindset, and is willing to take on any challenge.

1. Coding to model optimization
2. Model quantization
3. Participate in design, implementation, and execution across a variety feature including building ML/DL models.
4. Analyze complex, high-volume, high-dimensionality data.
5. Participate in designing and building Responsible AI harmful content model core.
6. Collaborate with a team of world-class researchers, scientists & engineers to solve very challenging problems.

Other:

• Embody our and