Machine Learning Engineer Intern

Key Skills

Design of Experiment, Large data sets, Machine learning techniques, Python Programming, Statistical modeling

Job Description

As a Machine Learning Engineer Intern, you will be part of a diverse team of engineers developing next-generation, vertically integrated products and services at Viasat. You will develop novel algorithms and techniques for analyzing complex data sets collected during Viasat’s product and service lifecycles. You will help define and develop models that produce new inferences and enable action by adjacent teams. You will work with software engineers to create new tools, libraries, and services that can expand Viasat’s ability to understand these complex data sets. You will be part of a growing team developing cloud-based solutions for tackling problems found at the cutting edge of technological development and manufacturing.

On this team, you will build a breadth of knowledge including distributed systems, predictive analytics, and machine learning. You will design, develop, and deploy analytic pipelines to answer questions across multiple business areas and disciplines for Viasat’s broad but vertically integrated products. We encourage learning through curiosity, immersion, collaboration, and action. We value adaptability and learning agility. Our ideal candidate is someone focused on solving tough problems using data and who loves doing so.

As a Machine Learning Engineer Intern, you will contribute with:

• Analytics: Architect, design, and build data analysis pipelines working with large and complex data sets to monitor and analyze metrics
• Inference: Use statistical tools to design experiments and determine causality
• Algorithms: Design and create predictive and decision-making machine learning models for various business needs
• Data engineering: Transforming and understanding data from many systems

Requirements

• Currently pursuing a Bachelor's degree or higher in Data Science, Applied Mathematics, Computer Science, Computer Engineering, Physics, or related field
• Experience with several statistical and machine learning models
• Experience with software development in Python
• Able to commit to a 10-12 week summer internship

Preferences

• Pursuing a MS/PhD in a data-related field such as applied mathematics, computer science, computer engineering, physics, or similar
• Knowledge of RF engineering, RF electronics, integrated circuits, electronics manufacturing, or digital communication systems
• Interest in or desire to work on anomaly detection, broadly defined
• Knowledge of or Interest in learning Bayesian approaches

Additional Requirements and Information

Minimum Education: High School Diploma or GED

Years of Experience: 0-2 years

Travel: None

Citizenship: US Citizenship required

Worker Classification: Intern