Applied Scientist: PhD Internship Opportunities

Microsoft; Redmond (WA); On-site; USD 70,196 - 135,817; Full time

Job summary

Microsoft is offering an internship for an Applied Scientist in Redmond, Washington. Candidates should be pursuing a Doctorate in Statistics or Computer Engineering. You will analyze algorithms, design experiments, and implement AI prototypes in a collaborative environment.

The role focuses on statistical modeling and requires proficiency in programming languages like Python. An innovative mindset is essential to tackle real-world challenges in machine intelligence.

This opportunity provides a competitive salary ranging from $6,290 to $12,170 monthly, alongside potential benefits.

Qualifications

• Pursing a Doctorate Degree in relevant fields.
• One additional quarter/semester left after internship.
• Experience with statistical modeling and deep learning.

Responsibilities

• Analyze and improve performance of algorithms on datasets.
• Design experiments for machine learning tasks.
• Implement prototypes in AI applications.

Skills

Statistical modeling

Deep learning frameworks

Python coding

Data structures

Machine Learning algorithms

Education

Currently pursuing a Doctorate Degree

Tools

PyTorch

TensorFlow

Keras

Hadoop

Spark

Job description

Overview

Come build community, explore your passions and do your best work at Microsoft with thousands of students from every corner of the world. This opportunity will allow you to bring your aspirations, talent, potential—and excitement for the journey ahead.

At Microsoft, Interns work on real‑world projects in collaboration with teams across the world, while having fun along the way. You’ll be empowered to build community, explore your passions and achieve your goals. This is your chance to bring your solutions and ideas to life while working on cutting‑edge technology.

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.

Please note this application is only for internships based in our Redmond, Washington office. For internships in other offices in the United States, please see our Careers site.

Qualifications

Required Qualifications

• Currently pursuing a Doctorate Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
• Must have at least one additional quarter/semester of school remaining following the completion of the internship

Preferred Qualifications

• Experience with statistical modeling and deep learning especially with frameworks such as PyTorch, Tensorflow or Keras.
• Proficient coding in one or more languages (e.g., Python, C# or similar)
• A background in data structures, algorithms and analysis of algorithm complexity
• Understanding of ML frameworks: TensorFlow, Keras, PyTorch, or Caffe
• Understanding of big data tools: Hadoop, Spark, Hive, or Cassandra.
• Specialized experience in one or more of these areas: Natural Language Understanding, Neural Networks, Computer Vision, Machine Learning, Deep Learning, Algorithmic Foundations of Optimization, Large Language Models, Data Mining, Machine Intelligence (Artificial Intelligence) or related fields

The base pay range for this internship is USD $6,290 - $12,170 per month. 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 $8,060 - $13,240 per month.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-intern-pay

Responsibilities

Applied Scientist Interns will:

• Analyze and improve performance of advanced algorithms on large‑scale datasets and cutting edge research in machine intelligence and machine learning applications.
• Think through the product scenarios and goals, identify key challenges, then fit the scenario asks into ML tasks, design experimental process for iteration and optimization.
• Implement prototypes of scalable systems in AI applications
• Gain an understanding of a broad area of research and applicable research techniques, as well as a basic knowledge of industry trends and share your knowledge with immediate team members