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Applied Scientist II at Microsoft
Redmond, Washington, United States -
Full Time

Start Date

Immediate

Expiry Date

19 Feb, 26

Salary

0.0

Posted On

21 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Machine Learning, Data Cleaning, Feature Engineering, Model Training, Model Evaluation, A/B Testing, Statistics, Predictive Analytics, Research, Publications, Production Systems, Production-Grade Code, Audio Signal Processing, Human-AI Interaction, Collaboration, Prototyping

Industry

Software Development

Description
Collaborating with AI researchers and audio signal processing experts to design and build end-to-end machine learning (ML) systems, tuned for human-human and human-AI interactions. Design and develop machine learning (ML) pipelines involving data cleaning, feature engineering, model training, and evaluation. Work across the product lifecycle from prototyping to shipping production-grade code optimized for performance and memory and updating the deployed models based on A/B testing. Remain up to date with latest advancements, trends and research and contribute towards our IP portfolio. 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. 2+ years of experience in development/deployment of machine learning algorithms. 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers). Experience explaining complex ideas to technical and non-technical audiences. Experience contributing code to production systems or shipped products. Experience building and maintaining production-grade ML (machine learning) pipelines.
Responsibilities
Collaborate with AI researchers and audio signal processing experts to design and build end-to-end machine learning systems. Develop ML pipelines, optimize performance, and update deployed models based on A/B testing.