Machine Learning Engineer
Redmond, Washington, United States
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Overview
Come build community, explore your passions and do your best work at Microsoft. This opportunity will allow you to bring your aspirations, talent, potential and excitement for the journey ahead.
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 Machine Learning, Cognitive Services, and the global Azure AI infrastructure for running the largest AI workloads on the planet.
Within AI Platform, our team in Evaluation AI is working on cutting-edge Natural Language Processing and Deep Learning models and building the next generation model evaluation platform.
We are looking for a passionate, creative, analytical Software Engineer who loves Natural Language Processing, deep learning and wants to ship products quickly at a massive scale. We will provide a lot of opportunities for you to learn, grow and contribute.
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.
Relocation assistance is not available for this role.
Qualifications
Required Qualifications:
- Bachelor's Degree in Computer Science, or related technical discipline with proven experience coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR equivalent experience
Background Check 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 (or currently pursuing) in Computer Science or related technical field AND 1+ year(s) technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR Master's Degree (or currently pursuing) 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
- OR Master's Degree (or currently pursuing) 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
- Proficient ML, statistics, and data science experience are a plus.
- Passion and experience to build large-scale AI models as general AI services to empower many organizations and people.
Software Engineering IC2 - The typical base pay range for this role across the U.S. is USD $81,900 - $160,200 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 $105,600 - $174,600 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 March 13, 2025.
Responsibilities
- Work on architecture, design and development of the next generation of Azure AI’s evaluation platform.
- Work with other researchers, applied scientists, and machine learning engineers in the team to design and build the end-to-end pipelines covering model training, data analysis, model serving and model evaluation.
- Implement latest evaluation methods from published literature and methods in the industry.
- Drive new product features and evaluation metrics.
