We are seeking a highly motivated and talented Senior Applied Scientist to join our Research Science and Strategy team. Our team, graduating from Microsoft Research and Incubation, is at the forefront of developing cutting-edge Artificial Intelligence (AI) solutions for enterprises using Generative AI. We are uniquely positioned to scale platform solutions that combine deep science and Artificial Intelligence to tackle challenges in various domains such as drug discovery, clean energy, and material science.
As a Senior Applied Scientist, you will be part of a multidisciplinary team that partners with a selected group of strategic partners to co-innovate and drive breakthroughs in deep science and AI. You will have the opportunity to work on state-of-the-art technologies, including generative AI, interpretable Machine Learning (ML) models and large-scale multi-modality model training and production. Furthermore, you will have the chance to engage with customers and owe the problem end-to-end from ideation to production.
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
Bringing the State of the Art to Products
Brings new technology and approaches into production by applying long-term research efforts to solve immediate product needs. Collaborates with and bridges the gap between researchers (in community across the company, Microsoft Research [MSR], or in their own organizations) and development teams. Begins to negotiate across teams to ensure cutting edge technology is being applied to products in a practical way that meets key business objectives. Develops an understanding of research approaches used across a group or organization to leverage (and not re-invent) solutions.
Independently works to create product impact. Identifies approach, and applies, improves, or creates a research-backed solution (e.g., novel, data driven, scalable, extendable) to positively impact a Microsoft product or service. Designs an approach to solve significant business problems shared by a senior team member. May publish research to promote receiving new intellectual property for product impact.
- Collaborate with a multidisciplinary team to develop cutting-edge AI solutions for various industries.
- Conduct research and development in generative AI, multi-modality models, training, and production.
- Collaborate with strategic partners to co-innovate and drive breakthroughs in deep science.
- Directly engage with customers to understand their needs and provide tailored AI solutions.
- Own the problem end-to-end, from ideation to production, ensuring successful implementation.
Leveraging Applied Research
Masters one or more subareas (e.g., Object Recognition, Text Classification) and gains expertise in a broad area of research (e.g., Machine Learning, Natural Language Processing, Computer Vision, Statistical Modeling, Data-Driven Insights. Understands the corresponding literature and applicable research techniques. Uses expertise to identify the right technique to use when examining a problem.
Research and develop an understanding of tools, technologies, and methods being used in the community that can be utilized to improve product quality, performance, or efficiency. Apply deep subject matter expert knowledge around several specialized tools/methods to support business impact.
Documentation
Performs documentation of work in progress, experimentation results, plans, etc. Documents scientific work to ensure process is captured. Creates informal documentation and may share findings to promote innovation within groups or with other groups.
Ethics and Privacy
Uses deep understanding of fairness and bias. May contribute to ethics and privacy policies related to research processes and/or data/information collection by providing updates and suggestions around internal best practices. Seeks to identify potential bias in the development of products.
Specialty Responsibilities
Leverages data analysis knowledge to clean, transform, analyze, integrate, and organize data to the level required by the analysis techniques selected. Develops useable datasets for modeling purposes. Scales the feature ideation and data preparation. Takes cleaned or raw data and adapts data for machine learning purposes. Uses understanding which features are important that come out of the model and identifies the optimal features. Identifies gaps in current datasets and drives onboarding of new datasets. Works with team to optimize signal system design. Mentors and coaches are less experienced members in data cleaning and analysis best practices. Identifies gaps in current datasets and drives onboarding of new datasets (e.g., bringing on third-party datasets). Attempts to fix bugs in data to inform developers how to improve the products. Ensures representative data to honor problem definition and ethics. *
Help address scalability problems by adjusting to stakeholder needs. Works with large-scale computing frameworks, data analysis systems, and modeling environments to improve models. Applies the model to real products, and then verifies effects through iterations. Experiments by putting multiple models in production and evaluating their performance. Mentors less experienced team members through modeling processes. Continues to monitor how algorithms perform against expected behaviors and performance or accuracy guardrails. Monitors over time for input and output data that there are changes over time. Uses system to run analyses on an ongoing basis such as by comparing predicted value with actual value. Addresses models that break during production (e.g., due to input streams changing).
Other
Qualifications
Required/Minimum Qualifications
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ 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 3+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate 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 equivalent experience.
- 2 years of experience in AI, machine learning, and deep learning
Preferred Qualifications
- Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
- Proficient in Generative AI frameworks like Semantic Kernel, Langchain and LlamaIndex.
- Self-motivated and proactive, with a desire to learn and contribute to a multidisciplinary team.
- Experience with developing products with a focus on generative AI, interpretable models, multi-modality models, and large-scale model training and production.
- Excellent communication and interpersonal skills, with the ability to engage with customers and strategic Partners.
Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $112,000 - $218,400 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 $145,800 - $238,600 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 and processes offers for these roles on an ongoing basis.
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.
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