Description
Summary
Microsoft AI are looking for a talented Applied Scientist II at their Redmond office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.
About the Role
As an Applied Scientist II, you will be responsible for building and maintaining production machine learning models to generate image and text assets, multimodal representation and predict ad quality. You will find insights and form hypothesis on web-scale data with various machine learning, computer vision, feature engineering, statistical, and data mining techniques. You will design experiments, understand the resulting data, and produce actionable, trustworthy conclusions from them. You will craft and optimize prompts for effective LLM and VLM performance, and wrangle large amounts of data using various tools.
Accountabilities
- Building and maintaining production machine learning models to generate image and text assets, multimodal representation and predict ad quality.
- Finding insights and forming hypothesis on web-scale data with various machine learning, computer vision, feature engineering, statistical, and data mining techniques.
The Candidate we're looking for
Experience:
- 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.
Technical skills:
- Experience with Large Language Models: Demonstrated experience working with LLMs/VLMs, such as GPT, BERT, or similar models, including knowledge of their strengths, limitations, and capabilities.
- Solid Understanding of NLP and CV: In-depth knowledge of natural language processing (NLP) and computer vision techniques and concepts, including tokenization, semantic analysis, and text generation, multimodal representation, etc.
Personal attributes:
- Experience delivering, scaling, and maintaining highly successful and innovative machine learning products with your fingerprints all over them.
- Experience in parallel or distributed processing, high performance computing, stream computing and SCOPE.
Benefits
- Competitive salary and benefits package.
- Opportunities for professional growth and development.
- Collaborative and dynamic work environment.