Principal Applied Scientist

Do you want to be part of a team which delivers innovative products and machine learning solutions across Microsoft to hundreds of millions of users every month? Microsoft Turing team is an innovative engineering and applied research team working on state-of-the-art deep learning models, large language models and pioneering conversational search experiences. The team spearheads the platform and innovation for conversational search and the core copilot experiences across Microsoft’s ecosystem including BizChat, Office and Windows.

As a** Principal Applied Scientist** in the Turing team, you be pushing & delivering on multiple tight timeline-based hands on data science activity and work, including training models, creating evaluation sets, building infrastructure for training and evaluation, and more. This will involve coordinating & aligning with internal & external data science, product & engineering teams across timezones.

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**:
As a Principal Applied Scientist on our team, you'll be responsible for and will engage in:

- Driving projects from design through conception, implementation, experimentation and finally shipping to our users. This requires deep diving into data to identify gaps, coming up with heuristics and possible solutions, using LLMs to create the right model or evaluation prompts, and setting up the engineering pipeline or infrastructure to run them.
- Documenting progress & processing, assisting & guiding junior team members, aligning & unblocking them with other stakeholders in timezones.
- Coming up with evaluation techniques, datasets, criteria and metrics for model evaluations. These are often SOTA models or metrics / datasets.
- Hands on pre-training, fine-tuning, use of language models, including dataset creation, filtering, review, and continuous iteration. This may also require understanding of training frameworks, formats, checkpoints, stacks such as megatron.

This requires working in a diverse geographically distributed team environment where collaboration and innovation are valued. You will have an opportunity for direct impact on design, functionality, security, performance, scalability, manageability, and supportability of Microsoft products that use our deep learning technology.

**Qualifications**:
**Required Qualifications**:

- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 12+ 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 10+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
- At least 3+ years of experience delivering team level outcomes.
- 2+ years of industrial experience coding in C++, C#, C, Java or Python.
- Prior experience with data analysis or understanding, looking at data from a large-scale systems to identify patterns or create evaluation datasets.
- Familiarity with common machine learning, deep learning frameworks and concepts, using use of LLMs, prompting.
- Ability to communicate technical details clearly across organizational boundaries.

**Preferred Qualifications**:

- 5+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
- 2+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.

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