Applied Scientist II
Redmond, Washington, United States
Full Time Mid-level / Intermediate USD 94K - 198K
Microsoft
We are looking for Applied Scientist II at Microsoft 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 Cognitive Services team empowers developers and data scientists around the world and of all skill levels to easily add AI capabilities to their apps.
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.
Responsibilities
- You will be a technical leader, working closely with colleagues and customers from various business domains drive Responsible AI product innovation.
- Drive innovations in Hallucination Detection and Mitigation models and algorithms where keep engineering resource consumption in mind.
- Lead and participate in design, implementation, and execution across a variety of feature including building Machine Learning/Deep Learning (ML/DL) models.
- Analyze complex, high-volume, high-dimensionality data.
- Participate in designing and building Responsible AI harmful content model core.
- Collaborate with a team of world-class researchers, scientists & engineers to solve very challenging problems.
- Invest in others’ growth.
- Embody our culture and values
Qualifications
Required/Minimum Qualifications:
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research)
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research).
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field.
- OR equivalent experience.
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:
- BS/MS in Computer Science, Statistics, Applied Mathematics, Physics, or other engineering or science fields and 5+ years industry experience in related fields or PhD with 3+ years industry experience.
- 3+ year experience in machine learning, deep learning and/or related fields.
- 3+ year experience in software development experience in languages such as Python, Java, C++, Scala, or C#.
- 1+ year experience developing end to end ML/DL engineering systems.
- 1+ year experience in distributed/cloud computing systems (e.g. Spark, Hadoop, Azure, AWS, Cosmos). 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.
- 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.
Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $94,300 - $182,600 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 $120,900 - $198,600 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 June 06, 2024.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
#aiplatform
Tags: AWS Azure Computer Science Data Analytics Deep Learning Econometrics Engineering Generative AI Hadoop Java Machine Learning Mathematics ML infrastructure ML models NLP OpenAI PhD Physics Python Research Responsible AI Scala Security Spark Statistics
Perks/benefits: Career development Medical leave Startup environment
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