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applied scientist - security research

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applied scientist security research

Microsoft

<div><b>Overview</b><p><br>
Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft&rsquo;s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers&rsquo; heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are looking for a senior applied scientist to join and shape the research and product roadmap for the team in this space.</p><p>
We are looking to hire a <b>Applied Scientist - Security Research,</b> you will have the opportunity to design and lead the implementation of advanced security solutions, leveraging cutting-edge machine learning and data-driven approaches to protect millions of users worldwide. You will collaborate with people at the forefront of their field from across the organization and see your ideas turn into reality with real-world impact at Microsoft scale. This is a hands-on role.</p><p>
Microsoft&rsquo;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.</p><b><br>
Responsibilities</b><br>
<ul><li>
Model development &amp; optimization. Design, develop, fine‑tune, and evaluate models, summarization, and reasoning</li><li>
Data &amp; evaluation at scale. Build/extend data pipelines for curation/labeling/feature stores; author offline eval harnesses; run A/Bs; define guardrails and success metrics.</li><li>
Production ML engineering. contribute to service code and configs; add monitoring, tracing, dashboards, and auto‑scaling; participate in on‑call and postmortems to improve live‑site reliability.</li><li>
Collaboration &amp; mentoring. Partner across PM/ENG/Research teams and beyond; identify AI technologies to create an adaptive and scalable solution to provide protection for our customers, share methods and code, review PRs, improve reproducibility and documentation; mentor junior scientists.</li><li>
Prototype end to end solutions (working in partnership with other stakeholders) to quickly prove out emergent technologies.</li><li>
Seek out experts across Microsoft and industry to learn about potential solutions and bring back the best and most relevant to solve our most critical problems.</li><li>
Serves as a subject matter expert by owning models and participate in oncall</li><li>
Let a deep empathy for customers guide you to improvements that make a tangible difference.</li></ul><br>
<b>
Qualifications</b><p><b><br>
Required/minimum qualifications</b></p><ul><li>
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)<ul><li>
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field</li><li>
OR equivalent experience.<div><p><b>
Other Requirements:</b></p><p>
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:</p><ul><li>
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.</li></ul><p><b>
Additional or preferred qualifications</b></p><ul><li>
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ 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)<ul><li>
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)</li><li>
OR equivalent experience.</li></ul></li><li>
1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).</li></ul><ul><li><p>
1+ years experience bringing new technology and approaches into production by applying long-term research efforts to solve immediate product needs.</p></li><li><p>
4+ years applied ML/NLP experience delivering models and features to production at scale.</p></li><li>
Languages and Technology - Python, R, C, SQL, Kusto / Azure Data Explorer, Power BI</li><li><p>
Experimentation &amp; evaluation: sound experimental design, metric design (quality, safety, latency, cost), and statistical analysis; experience running A/B tests.</p></li><li>
Proven collaboration with partners and stakeholders to integrate ML into shipped product and to drive measurable business impact.</li><li>
Experience with fraud/security a plus</li><li>
Experience with developing Agentic AI (Artificial Intelligence) in a COGS (Cost of Goods Sold) efficient manner</li><li>
Experience working across multiple product teams to deliver combined innovations and features and representing innovative work across the greater organization and/or the industry</li><li>
Able to deliver impact through collaborative work across organizational boundaries and thrive in an agile environment balancing committed work with emerging innovative solutions</li><li>
Model serving/inference (e.g., ONNX Runtime, vLLM, Triton, quantization, distillation, caching, dynamic batching, rate limiting).</li><li>
Experimentation: A/B &amp; interleavings, guardrail metrics (quality/safety/latency/cost), sequential testing, eval governance.</li></ul></div></li></ul></li></ul><br>
<br>
<br>
<p>Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 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 $131,400 - $215,400 per year.
</p><p></p><p>Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:<br>
https://careers.microsoft.com/us/en/us-corporate-pay</p><p><br>
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.</p><p></p><p><br>
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process<b>.</b></p></div>

Applied Scientist - Security Research

<div><b>Overview</b><p><br>
With continued growth in digital data and the desire to leverage data to address problems that touch all aspects of our lives, Microsoft&rsquo;s AI Platform is growing to meet these challenges! The AI Platform is hiring experienced engineers to join agile and diverse engineering teams in MAI.</p><p>
As an Applied Scientist in MAI, you would be responsible for data analysis, training and building models and shipping to production high quality experiences improving Bing products. This opportunity will allow you to accelerate your career growth, develop deep business acumen, hone your selling skills, and become adept at deal structuring.</p><p>
Microsoft&rsquo;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.
 </p><p>Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.</p><b><br>
Responsibilities</b><br>
<ul><li>
You will gain a basic understanding of a broad area of research and applicable research techniques. You&rsquo;ll also develop a basic knowledge of industry trends and share your knowledge with immediate team members.</li><li>
You will apply strategies provided by senior team members. Following guidance from team leaders you&rsquo;ll also research relevant tools and technologies being used in the community.</li><li>
You will reinforce a positive environment by learning and adopting best practices. And you will maintain or develop ties with an external network of peers and identify prospective talent for Microsoft research pipelines when asked.</li><li>
You will assist with documentation for senior team members, as needed. You&rsquo;ll also learn and follow ethics and privacy policies while executing research processes or collecting information.</li></ul><br>
<b>
Qualifications</b><p><b><br>
Required Qualifications:</b></p><ul><li>
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)<ul><li>
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)</li><li>
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field</li><li>
OR equivalent experience.</li></ul></li></ul><p><b>
Other Requirements:</b><br>
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:</p><ul><li><b>
Microsoft Cloud Background Check: </b>This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.</li></ul><p><br>
#MicrosoftAI</p><br>
<br>
<br>
<p>Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 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 $131,400 - $215,400 per year.
</p><p></p><p>Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:<br>
https://careers.microsoft.com/us/en/us-corporate-pay</p><p><br>
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.</p><p></p><p><br>
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process<b>.</b></p></div>

Applied Scientist

<div><b>Overview</b><p><br>
We&rsquo;re building a Frontier Marketing organization where the Media Data Science &amp; Analytics team leads the way in transforming how Microsoft measures, analyzes, and optimizes media and digital experiences. Our team blends advanced analytics, experimentation, and AI-powered insights to drive smarter decision making and measurable business outcomes across paid media and owned digital properties. We operate with agility, prioritize outcomes over activity, and embrace rapid learning loops to unlock deeper audience understanding, maximize impact, and accelerate innovation in media and discovery strategy.</p><p></p><p><br>
To support this transformation, we are seeking a Senior Data Scientist to lead advanced experimentation and causal inference efforts that enable rigorous campaign measurement and drive data-informed marketing decisions at scale. In this role, you'll directly support Microsoft's mission by enabling data-driven marketing decisions that drive customer engagement and revenue growth. Shape What You Will Do As a Senior Data Scientist on the Media Data Science and Analytics team, you will design and implement advanced experimentation frameworks including Bayesian hypothesis testing, causal inference modeling, and heterogeneous treatment effect analysis, while building and deploying Machine Learning (ML) models and data pipelines to support portfolio impact measurement and campaign analytics at scale. This will include developing solutions that are reusable, readily discoverable by decision makers, and self-service oriented, driving meaningful interpretation of data, and supporting campaign optimization.</p><p></p><p><br>
This candidate thrives in fast-paced environments, demonstrates comfort with ambiguity, and collaborates effectively across teams and functional boundaries. Curiosity, a bias for action, and the ability to balance business context with technical experience are essential. In this role, you will support the rhythm of business by providing actionable recommendations to stakeholders based on rigorous analysis and clear insights. You will leverage statistical and machine learning techniques to develop scalable, efficient, and impactful data products while also diving deep into the details to uncover the story behind the data. You will bring sharp analytical thinking, communication skills, and the confidence to engage with executives and stakeholders across the business.</p><p></p><p><br>
Microsoft&rsquo;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.</p><p>
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.</p><p></p><b><br>
Responsibilities</b><br>
<ul><li>
Experimentation and Causal Inference Design and implement advanced experimentation frameworks including Bayesian hypothesis testing and causal inference modeling.</li><li>
Develop heterogeneous treatment effect analyses to understand differential campaign impacts across customer segments.</li><li>
Establish clear linkage between A/B test results and desired business outcomes.</li><li>
Assess the degree to which campaigns meet business objectives and address gaps.</li><li>
Ensure alignment on definitions and standards across stakeholders.</li><li>
Define, design, and promote appropriate feedback and evaluation methods. Present results and findings to senior stakeholders.</li><li>
Build and deploy ML models to support portfolio impact measurement and campaign analytics at scale.</li><li>
Develop and maintain data pipelines that enable scalable, automated analysis.</li><li>
Evaluate the viability of automated methods for data collection, reporting, and analysis.</li><li>
Ensure solutions are reusable, easily discoverable, and self-service oriented.</li><li>
Identify and promote methods that enhance efficiency in analytics and reporting.</li><li>
Drive meaningful data interpretation to inform business decisions and shape organizational understanding through compelling storytelling.</li><li>
Recommend and socialize optimal methods for operationalizing, sharing, and scaling insights.</li><li>
Share knowledge and practical rationale for transitioning ad-hoc analyses to regular reporting features.</li><li>
Share domain knowledge to create clarity and ensure readiness to leverage data and insights effectively.</li><li>
Orchestration and Collaboration Leverage working relationships within and across teams to ensure alignment and quality execution.</li><li>
Drive the adoption of recommended data sources and analysis practices.</li><li>
Consult across teams and influence data strategy, experimentation culture, and measurement frameworks on decisions related to data sourcing, analyses, and interpretation of results.</li><li>
Coach and mentor less experienced analysts, as needed, and enable cross-functional partners to become data-savvy.</li><li>
Share insights and analytical experience through various means, including dashboards, reports, and visualizations.</li><li>
Synthesize and simplify details across analyses to highlight relevant findings. Identify opportunities to improve the efficiency of insights reporting techniques.</li><li>
Guide others and establish partnerships with stakeholders to ensure results are accessible and relevant.</li><li>
Embody our Culture and Values</li></ul><br>
<b>
Qualifications</b><p><b><br>
Required/minimum qualifications</b></p><ul><li>
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) experience in data science, applied statistics, machine learning, or quantitative research</li><li><ul><li>
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years experience in data science, applied statistics, machine learning, or quantitative research</li><li>
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years experience in data science, applied statistics, machine learning, or quantitative research</li><li>
OR equivalent experience.</li></ul></li></ul><p></p><p><b><br>
Additional or preferred qualifications</b></p><ul><li>
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years experience in data science, applied statistics, machine learning, or quantitative research</li><li><ul><li>
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years experience in data science, applied statistics, machine learning, or quantitative research</li><li>
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years experience in data science, applied statistics, machine learning, or quantitative research</li><li>
OR equivalent experience.</li></ul></li></ul><ul><li>
4+ years of experience with Python or R for statistical analysis and machine learning.</li><li>
4+ years of experience with SQL and data pipeline development.</li><li>
3+ years of experience designing and analyzing A/B experiments or causal inference studies.</li><li>
2+ years of experience with Bayesian methods, causal inference techniques (e.g., difference-in-differences, instrumental variables, propensity score matching), or heterogeneous treatment effect estimation.</li><li>
2+ years of experience building and deploying ML models.</li><li>
4+ years of experience presenting complex technical findings to both technical and non-technical senior level stakeholders.</li><li>
Experience with marketing mix modeling (MMM) or attribution modeling.</li><li>
Experience with cloud-based ML platforms (e.g., Azure ML, Databricks).</li><li>
4+ years' experience analyzing marketing campaign performance.</li><li>
Experience with Microsoft Fabric, Power BI, or similar visualization platforms.</li></ul><br>
<br>
<br>
<p>Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $158,400 - $258,000 per year.
</p><p></p><p>Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:<br>
https://careers.microsoft.com/us/en/us-corporate-pay</p><p><br>
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.</p><p></p><p><br>
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process<b>.</b></p></div>

Senior Data Scientist

<div><b>Overview</b><p><br>
We&rsquo;re hiring a Senior Applied Scientist with expertise in natural language processing (NLP), deep learning, and Ads recommender systems in Redmond, WA or Mountain View, CA.</p><p>
In this role, you will design and implement cutting-edge machine learning models and algorithms that power relevance systems across all surfaces for Microsoft Ads and Shopping including Bing, Copilot, and beyond.</p><p>
You will have a direct impact on millions of users and advertisers, delivering scalable solutions to enhance ad relevance and optimize user experiences. This role is part of Microsoft Artificial Intelligence (MAI)-Ads Engineering and is responsible for the end-to-end relevance problem for our ads and shopping products.</p><p>
Microsoft&rsquo;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.</p><p>
Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.</p><b><br>
Responsibilities</b><br>
<ul><li>
Own high‑impact and open-ended relevance problem areas across Product Ads and Shopping including providing strategic direction to solve problems and applying deep subject matter knowledge to support business impact.</li><li>
Drive algorithmic and modeling improvements to the system using primarily deep learning techniques from NLP and computer vision, including latest LLM models, to deliver clear and measurable product impact</li><li>
Exercise solid technical judgment on metrics, evaluation strategies, and tradeoffs optimizing for overall product ROI rather than isolated metrics.</li><li>
Act as a technical leader and mentor, providing design reviews and documenting to share modeling guidance and evaluation best practices for other applied scientists to promote innovation.</li><li>
Collaborate deeply across disciplines (Engineering, PM, Research, Data Science), translating scientific intent into production‑ready systems and constraints.</li><li>
Operate with high independence and accountability, anticipating risks, planning for unknowns, and requiring minimal oversight to deliver sustained impact at scale.</li><li>
Use your deep understanding of fairness and bias to contribute to ethics and privacy policies related to research processes and data collection.</li></ul><br>
<b>
Qualifications</b><p><b><br>
Required Qualifications:</b></p><ul><li>
Bachelor's Degree in Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering or related field AND 4+ years related experience (e.g., statistics predictive analytics, research)<ul><li>
OR Master's Degree in Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
</li><li>OR Doctorate in Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)</li><li>
OR equivalent experience.</li></ul></li></ul><p><b>
Preferred Qualifications:</b></p><ul><li>
Data Science, Machine Learning, Statistics, Computer Science 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)<ul><li>
OR equivalent experience.</li></ul></li><li>
4+ years working experience in statistical natural language processing (NLP) with the latest deep learning technologies including transformer and LLMs OR 4+ years working experience in Computer Vision (CV) with latest deep learning technologies including Vision Transformers.</li><li>
4+ years working experience with coding in production systems using C++, C#, Java or Python.</li></ul><p>
#MicrosoftAI</p><br>
<br>
<br>
<p>Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $158,400 - $258,000 per year.
</p><p></p><p>Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:<br>
https://careers.microsoft.com/us/en/us-corporate-pay</p><p><br>
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.</p><p></p><p><br>
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process<b>.</b></p></div>

Senior Applied Scientist

<div><b>Overview</b><div><p><br>
Excel is one of the most widely used and impactful software programs in the world, powering solutions for businesses and individuals across every industry. We are seeking a <b>Principal Applied Science Manager</b> to join the <b>Excel Core team</b>&mdash;an opportunity to shape the future of productivity and influence hundreds of millions of users globally. Your mission: bring cutting-edge Artificial Intelligence (AI) technologies, patterns, and model capabilities into production, delivering intelligent experiences directly in the Excel grid.</p><p>
As a <b>Principal Applied Science Manager</b>, you will work at the intersection of research and engineering&mdash;leading an Applied Science team, writing production-quality code, collaborating with researchers and engineers, and fostering a culture of rapid experimentation that ships. You&rsquo;ll help define the next generation of AI-powered features in Excel, blending scientific rigor with engineering excellence to create experiences that delight users and transform workflows.</p><p>
Opportunities in Excel:</p><ul><li>
AI-Powered Intelligence in the Grid: Design and deliver Copilot‑powered contextual experiences that improve customer workflows through inline, intelligent assistance. Build scalable systems that anticipate user needs and surface relevant guidance to help users complete their tasks efficiently.</li><li>
Develop innovating new functions using Copilot to mix the power of AI with the versatility and richness of the Excel Calculation engine.</li><li>
Core Platform Innovation: Excel core functionality and fundamentals, including the Calculation Engine, Collaboration Experiences, Performance and Accessibility.</li><li>
Data Visualization &amp; Business Intelligence: Reinvent how users interact with data through PivotTables, Charting, and new Copilot-driven insights.</li><li>
Cloud-Scale Architecture: Re-architect the service-backed infrastructure that powers collaboration, Copilot, and core cloud capabilities by optimizing file storage and service protocols.</li><li>
Strategic Enterprise Partnerships: Work closely with high-impact customers to refine and extend Excel&rsquo;s platform with a focus on the core fundamentals&mdash;calculation, collaboration, reliability, and performance.</li></ul><p>
Microsoft&rsquo;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.</p></div><b><br>
Responsibilities</b><br>
<div><ul><li>
Defining, leading, and helping to conduct research projects that simultaneously advance the state-of-the-art and directly benefit Microsoft&rsquo;s core productivity products.</li><li>
Drive complex orchestration of Copilot workflows and agent pipelines, blending prompt engineering, tool invocation, and context grounding for productivity scenarios.</li><li>
Contribute to the end-to-end development, deployment, and continuous improvement of advanced multimodal machine learning (ML)/ large language model (LLM) systems&mdash;including dataset curation, labeling strategy, model architecture, scalable training, and rigorous evaluation (offline and online).</li><li>
Stay current with research and industry trends, identifying opportunities to integrate emerging technologies and methods into the Excel Core ecosystem across the entire spectrum of AI adoption.</li><li>
Effectively communicating with product leaders (and often Microsoft researchers (MSR)) throughout the planning and execution of applied research projects, which often involves learning and teaching complex concepts.</li><li>
Collaborate with engineering and product teams to define success metrics, design and execute experiments (e.g., A/B testing), monitor user signals, and iterate on deployed features.</li><li>
Embody our culture and values.</li></ul></div><br>
<b>
Qualifications</b><p><b><br>
Required Qualifications:</b></p><div><ul><li>
Bachelor'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)<ul><li>
OR Master'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)</li><li>
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).</li><li>
OR equivalent experience.</li></ul></li><li>
1+ year(s) of people management experience.</li></ul><p><b>
Other Requirements:</b></p><p>
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:</p><ul><li><b>
Microsoft Cloud Background Check: </b>This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.</li></ul><p><b>
Preferred Qualifications:</b></p><div><ul><li>
Experience orchestrating LLM-based agent pipelines - prompt engineering, tool invocation, context grounding and evaluation - for productivity scenarios, alongside other advanced ML techniques.</li><li>
Advanced degree (Master or PhD) in Computer Science, Math, Statistics, or related areas with industry experience or research publication in LLMs, ML, or Natural language processing (NLP).</li><li>
Proven expertise and background in designing and implementing AI models that serve millions of users in scaled production environments or agent-based workflows for real-world productivity applications.</li><li>
Demonstrated success moving applied research into shipped product features, with clear ownership of the end-to-end ML lifecycle&mdash;data collection, cleaning, modeling, evaluation, prompt engineering and continuous improvement.</li><li>
Experience coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.</li><li>
Deep understanding of transformer-based architectures and hands-on experience with model optimization techniques (quantization, pruning, distillation, adapter tuning).</li><li>
Customer-obsessed mentality and passion for translating research breakthroughs into meaningful product impact.</li><li>
Experience in designing and debugging complex services.</li><li>
Ability to communicate and collaborate with multiple teams.</li></ul><p></p><div><br>
#appliedsciences
<br>
#appliedscientist
<br>
#excelcore</div></div></div><br>
<br>
<br>
<p>Applied Sciences M5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 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 $188,000 - $304,200 per year.
</p><p></p><p>Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:<br>
https://careers.microsoft.com/us/en/us-corporate-pay</p><p><br>
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.</p><p></p><p><br>
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process<b>.</b></p></div>

Principal Applied Science Manager - Excel Core

<div><b>Overview</b><div></div><div><div><p><br>
As a <b>Senior Research Engineer</b> at Microsoft, you will advance Microsoft&rsquo;s mission to empower every person and every organization to achieve more. You will help build and integrate cutting-edge AI into Microsoft products and services within <b>Experience + Devices</b> (E+D) org, ensuring solutions are inclusive, ethical, and impactful. This role blends applied research, machine learning engineering, and product innovation. You will lead efforts to ship reliable, production-grade AI systems across the stack, from model development and fine-tuning to performance optimization and deployment.</p></div><div><p>
We are in an era of unprecedented AI innovation. As Microsoft leads the way in foundation models, multimodal systems, and AI agents, our goal is to build an open architecture platform where users can interact with tailored AI agents that drive tangible, real-world outcomes. As a Senior Research Engineer, you will:</p></div><div><ul><li><p>
Bridge the gap between state-of-the-art research and customer-facing features</p></li></ul></div><div><ul><li><p>
Drive systems-level innovation across models, infrastructure, and deployment</p></li></ul></div><div><ul><li><p>
Champion responsible AI by embedding fairness, safety, privacy, and performance from the ground up</p></li></ul></div></div><b><br>
Responsibilities</b><div><div><p><b><br>
Bringing State-of-the-Art Research to Products</b></p></div><div><ul><li><p>
Design and implement AI systems using foundation models, prompt engineering, retrieval-augmented generation, multi-agent architectures, and classic ML</p></li></ul></div><div><ul><li><p>
Fine-tune large language models on domain-specific data and evaluate via offline and online methods such as A/B testing, telemetry, and shadow deployments</p></li></ul></div><div><ul><li><p>
Build and harden prototypes into production-ready services using robust software engineering and MLOps practices</p></li></ul></div><div><ul><li><p>
Drive original research and thought leadership (whitepapers, internal notes, patents); convert insights into shipped capabilities</p></li></ul></div><div><ul><li><p>
Research Translation: Continuously review emerging work; identify high-potential methods and adapt them to Microsoft problem spaces</p></li></ul></div><div><p><b>
End-to-End System Development</b></p></div><div><ul><li><p>
ML Design &amp; Architecture: Own end-to-end pipeline from data prep, training, evaluation, deployment, and feedback loops</p></li></ul></div><div><ul><li><p>
Identify and resolve model quality gaps, latency issues, and scale bottlenecks using PyTorch, or TensorFlow</p></li></ul></div><div><ul><li><p>
Operate CI/CD and MLOps workflows including model versioning, retraining, evaluation, and monitoring</p></li></ul></div><div><ul><li><p>
Integrate AI components into Microsoft products in close partnership with engineering and product teams</p></li></ul></div></div><div><div><p><b>
Data-Driven Innovation</b></p></div><div><ul><li><p>
Evaluation &amp; Instrumentation: Build robust offline/online evals, experimentation frameworks, and telemetry for model/system performance.</p></li></ul></div><div><ul><li><p>
Learning Loop Creation: Operationalize continuous learning from user feedback and system signals; close the loop from experimentation to deployment.</p></li></ul></div><div><ul><li><p>
Experimentation &amp; E2E Validation: Design controlled experiments, analyze results, and drive product/model decisions with data.</p></li></ul></div><div><ul><li><p>
Develop proofs of concept that validate ideas quickly at realistic scales</p></li></ul></div><div><ul><li><p>
Curate high-signal datasets, including synthetic and red-team corpora, and establish labeling protocols and data quality checks tied to evaluation KPIs</p></li></ul></div><div><p><b>
Cross-Functional Collaboration</b></p></div><div><ul><li><p>
Partner with software engineers, scientists, designers, and product managers to deliver high-impact AI features</p></li></ul></div><div><ul><li><p>
Translate research breakthroughs into scalable applications aligned with product priorities</p></li></ul></div><div><ul><li><p>
Communicate findings and decisions through internal forums, demos, and documentation</p></li></ul></div><div><p><b>
Responsible AI &amp; Ethics</b></p></div><div><ul><li><p>
Identify and mitigate risks related to fairness, privacy, safety, security, hallucination, and data leakage</p></li></ul></div><div><ul><li><p>
Uphold Microsoft&rsquo;s Responsible AI principles throughout the lifecycle</p></li></ul></div><div><ul><li><p>
Contribute to internal policies, auditing practices, and tools for responsible AI</p></li></ul></div><div><p><b>
Operating Altitudes</b></p></div><div><ul><li><p>
Paper level (ideas and math): Read, critique, and adapt the latest research; identify gaps; design methods with clear trade-offs and guarantees; communicate complex ideas clearly.<br>
Example: &ldquo;This objective is brittle under our data regime. Here is a tighter analysis and a revised loss we can test this sprint.&rdquo;</p></li></ul></div><div><ul><li><p>
Code level (implementation): Turn ideas into robust, tested, maintainable modules; integrate with CI/CD; profile and optimize for latency and throughput.<br>
Example: &ldquo;Refactored the prototype into a reusable PyTorch component, added unit tests and benchmarks, and cut P95 inference latency by 30%.&rdquo;</p></li></ul></div><div><p><b>
Specialty Technical Areas</b></p></div><div><ul><li><p>
Large-scale training and fine-tuning of LLMs, vision-language, or multimodal models</p></li></ul></div><div><ul><li><p>
Multi-agent systems, dialogue agents, and copilots</p></li></ul></div></div><div><div><ul><li><p>
Optimization of inference speed, accuracy, reliability, and cost in production</p></li></ul></div><div><ul><li><p>
Retrieval systems and hybrid architectures using RAG and vector databases</p></li></ul></div><div><ul><li><p>
ML for real-world data constraints such as missing data, noisy labels, and class imbalance</p></li></ul></div></div><b><br>
Qualifications</b><div><p><b><br>
Required Qualifications</b></p></div><div><ul><li><p>
Bachelor&rsquo;s degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field and 4 or more years in applied ML or AI research and product engineering,</p><ul><li>
OR Master&rsquo;s degree and 3 or more years in applied ML or AI research and product engineering,</li><li>
OR PhD in a relevant field and 2 or more years with generative AI, LLMs, or related ML algorithms</li></ul></li></ul></div><div><p><b>
Other Requirements</b></p></div><div><p>
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:</p><ul><li><b>
Microsoft Cloud Background Check:</b> This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.</li></ul></div><div><p><b>
Preferred Qualifications</b></p></div><div><ul><li><p>
PhD in AI/ML or related field with top-venue publications and/or patents</p></li></ul></div><div><ul><li><p>
Experience with Microsoft&rsquo;s LLMOps stack: Azure AI Foundry, Azure Machine Learning, Semantic Kernel, Azure OpenAI Service, and Azure AI Search for vector/RAG</p></li></ul></div><div><ul><li><p>
Familiarity with responsible AI evaluation frameworks and bias mitigation methods</p></li></ul></div><div><ul><li><p>
Experience across the product lifecycle from ideation to shipping</p></li><li><p>
Proficiency in Python and at least one deep learning framework such as PyTorch, JAX, or TensorFlow</p></li><li><p>
Experience deploying Fine Tuned LLMs or multimodal models in live production environments</p></li><li><p>
Experience shipping and maintaining production AI systems</p></li></ul><div>
#CXAJOBS</div><div>
#BICJOBS</div></div><br>
<br>
<br>
<p>Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $158,400 - $258,000 per year.
</p><p></p><p>Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:<br>
https://careers.microsoft.com/us/en/us-corporate-pay</p><p><br>
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.</p><p></p><p><br>
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process<b>.</b></p></div>

Senior Research Engineer

Nintendo

<div><p><b>Nintendo Technology Development</b></p>
<p>
The worldwide pioneer in the creation of interactive entertainment, Nintendo Co., Ltd., of Kyoto, Japan, manufactures and markets hardware and software for its Nintendo Switch&trade; system and the Nintendo 3DS&trade; family of portable systems. Since 1983, when it launched the Nintendo Entertainment System&trade;, Nintendo has sold more than 4.7 billion video games and more than 740 million hardware units globally, including Nintendo Switch and the Nintendo 3DS family of systems, as well as the Game Boy&trade;, Game Boy Advance, Nintendo DS&trade; family of systems, Super NES&trade;, Nintendo 64&trade;, Nintendo GameCube&trade;, Wii&trade; and Wii U&trade; systems. It has also created industry icons that have become well-known, household names, such as Mario, Donkey Kong, Metroid, Zelda and Pok&eacute;mon. A wholly owned subsidiary, Nintendo Technology Development, based in Redmond, Washington, creates future hardware/software technology and researches North American-based technologies.</p>
<p>
Nintendo is an equal opportunity employer. We offer a welcoming and inclusive environment in service to one another, our products, the diverse consumers we represent, and the communities we call home. We do all of this with kindness, empathy and respect for each other.</p>
<div>
<div><div><div><b>DESCRIPTION OF DUTIES</b></div>
<ul><li>Train, evaluate, and optimize neural networks</li>
<li>Write scripts to facilitate neural network model development and use</li>
<li>Procure and clean data necessary for training and evaluating models</li>
<li>Effectively communicate with other teams, especially as it relates to domain-specific knowledge, model quality, and model performance</li>
<li>Document work according to defined processes</li>
</ul></div></div></div><div><div><div><div><b>SUMMARY OF REQUIREMENTS:</b></div>
<ul><li>3+ years of professional experience as a data scientist</li>
<li>3+ years of professional experience working with deep learning libraries (PyTorch and/or TensorFlow)</li>
<li>Proficient in Python</li>
<li>Possess strong debugging and troubleshooting skills</li>
<li>Familiar with Git workflow</li>
<li>Experience with C, C++, or C# is a plus</li>
<li>BS in CS/Applied Mathematics/Statistics/DS/ML or related field</li>
</ul> <div>This position is onsite in Redmond, WA, and not open to remote status at this time.</div></div></div></div></div><p></p>

CONTRACT - Engineer, Data Scientist (NTD)

Explore 61+ Applied scientist security research in Redmond this March. Find roles across top companies and apply now to boost your career.