Senior Researcher
Microsoft
Job Overview
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Job Description
Overview
As a Senior Researcher in Applied Sciences Group, you will play a pivotal role in advancing Microsoft's mission to empower every individual and organization on the planet to achieve more. You will contribute to the development and integration of cutting-edge AI technologies into Microsoft products and services, ensuring they are inclusive, ethical, and impactful.
You will collaborate across product, research, and engineering teams to bring innovative solutions to life, applying your expertise in machine learning, data science, and AI to solve complex problems. Your work will directly influence product direction and customer experiences.
As Microsoft continues to lead in AI, we are seeking individuals to help tackle some of the most exciting and meaningful challenges in the field. Our vision is to build a truly open architecture platform that enables users to summon tailored AI agents to drive real-world outcomes.
This role will combine AI knowledge with applied science expertise, and demonstrate a growth mindset and customer empathy.
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
- Build collaborative relationships with product and business groups to deliver AI-driven impact.
- Research and implement state-of-the-art using foundation models, prompt engineering, graphs, multi-agent architectures, as well as classical machine learning techniques.
- Fine-tune foundation models using domain-specific datasets.
- Evaluate model behavior on relevance, bias, hallucination, and response quality via offline evaluations, shadow experiments, online experiments.
- Build rapid AI solution prototypes, contribute to production deployment of these solutions and debug production code.
- Contribute to papers, patents, and conference presentations.
- Translate research into production-ready solutions and measure their impact through A/B testing and telemetry that address customer needs.
- Ability to use data to identify gaps in AI quality, uncover insights and implement proof of concepts.
Qualifications
Required 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.
Preferred Qualification:
- 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- 1+ years of experience with generative AI OR LLM/ML algorithms.
- 1+ years of experience working with Generative AI models and ML stacks.
Key skills/competency
- Machine Learning
- Data Science
- AI Technologies
- Foundation Models
- Prompt Engineering
- Multi-agent Architectures
- A/B Testing
- Python
- Predictive Analytics
- Generative AI
How to Get Hired at Microsoft
- Research Microsoft's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Customize your resume: Tailor your resume to highlight experience in AI, machine learning, and data science, aligning with the Senior Researcher role.
- Showcase applied research: Prepare to discuss projects where you translated research into production-ready AI solutions with measurable impact.
- Demonstrate a growth mindset: Emphasize your ability to learn, adapt, and innovate, addressing complex challenges in AI development.
- Practice technical interviews: Be ready for questions on foundation models, prompt engineering, ML algorithms, and coding in Python.
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