Machine Learning Engineer Intern

US - AZ - Tempe, US - CA - Carlsbad, US - CA - San Jose, US - CO - Englewood, US - FL - Tampa, US - GA - Duluth, US - MA - Boston, US - MA - Marlborough, US - MD - Germantown, US - TX - Austin Ref #12685 01-Aug-2022

Job Description

One team. Global challenges. Infinite opportunities. At Viasat, we’re on a mission to deliver connections with the capacity to change the world. For more than 35 years, Viasat has helped shape how consumers, businesses, governments and militaries around the globe communicate. We’re looking for people who think big, act fearlessly, and create an inclusive environment that drives positive impact to join our team.

Job Responsibilities 

As a Machine Learning Engineer, you will be part of a diverse team of engineers developing next-generation, vertically integrated products and services at Viasat. You will develop new, novel algorithms and techniques for analyzing complex data sets collected during Viasat’s product and service lifecycles. You will be responsible for defining and developing 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 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.

On this team, you’ll 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 immersion, collaboration and action. We value adaptability and curiosity. Our ideal candidate is someone focused on solving tough problems using data and loves doing so. You will have a role in the training and education of your peers by providing technical guidance and supporting team member growth.

As a Machine Learning Engineer, you will contribute with:

Maintains responsibility for translating business requirements into objectives and problems to be solved using data science and machine learning optimization

Architect, design, and build data analysis pipelines working with large and complex data sets to monitor and analyze metrics

Use statistical tools to design experiments and determine causality

Design and create predictive and decision-making algorithms for various business needs

Transforming and understanding data from many systems

Presents technical solutions to business partners using their strong communication skill

Maintains responsibility for ensuring the delivered software product remains operational and that fresh data is ingested continually


Currently pursuing a Bachelor degree in a highly quantitative field (Computer Science, Engineering, Statistics, Mathematics, Physics or related field))

Experience with software development, machine learning and/or distributed systems.

Experience with Python,  SQL

Experience with visualization frameworks such as, Matplotlib, bokeh/seaborn, or similar.

Experience working with diverse and disparate datasets.

Ability to communicate and present data to technical & non-technical audiences


Experience building ML/DL models & supporting infrastructure (training & inference).

Experience with spatial/GIS processing (postgis, rasters/GDAL, pyproj, shapely)

Experience with docker, ansible, airflow

Knowledge of communication & networking protocols

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Additional Requirements and Information

Minimum Education
High School Diploma or GED
Years of Experience
0-2 years
Up to 10%
Worker Classification

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Viasat is proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, ancestry, physical or mental disability, medical condition, marital status, genetics, age, or veteran status or any other applicable legally protected status or characteristic.

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