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Machine Learning Sports Jobs (NOW HIRING)

Swish Analytics

Machine Learning Engineer

San Francisco, CA · On-site +1

$160K/yr

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of ... The Data Science team is hiring an experienced Machine Learning Engineer with a background building ...

Extend

Manager, Machine Learning

$180K - $210K/yr

... sports and fitness, and much more. Extend is backed by some of the most prominent technology ... Required: * 6+ years of work experience building and deploying machine learning systems into ...

AEG Presents

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues ... As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize ...

AEG

Staff Machine Learning Engineer

Atlanta, GA · On-site

$220K - $280K/yr

As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues ... As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize ...

PrizePicks

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues ... As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize ...

Sofascore

$115K - $158K/yr

ABOUT SOFASCORE Sofascore is a sports-tech company created with one goal in mind - giving sports ... We are looking for an experienced Senior Machine Learning Engineer to join our AI Team. This is a ...

Paramount

Principal Machine Learning Engineer

Manhattan, NY · On-site

$245K - $367K/yr

This position shapes how millions of viewers discover films, series, live sports, and news on ... Own end-to-end machine learning pipelines-from data and feature engineering to training, deployment ...

PrizePicks

Machine Learning Platform Engineer

Atlanta, GA · On-site +1

$135K - $160K/yr

As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues ... Design and build the end-to-end machine learning infrastructure, setup platform for transitioning ...

AEG

Machine Learning Platform Engineer

Atlanta, GA · On-site

$135K - $160K/yr

As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues ... Design and build the end-to-end machine learning infrastructure, setup platform for transitioning ...

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Machine Learning Sports information

What is the difference between Machine Learning Sports vs Data Scientist?

AspectMachine Learning SportsData Scientist
Required CredentialsBachelor's or master's in sports analytics, computer science, or related fields; knowledge of sports data and machine learningBachelor's or master's in statistics, computer science, or related fields; strong programming and analytical skills
Work EnvironmentSports teams, athletic organizations, sports analytics firmsVarious industries including finance, healthcare, tech; corporate or research settings
Employer & Industry UsagePrimarily in sports industry for performance analysis and player scoutingAcross multiple industries for data analysis, predictive modeling, and decision-making

Machine Learning Sports focuses on applying machine learning techniques specifically to sports data for performance and strategy insights, while Data Scientists work across diverse industries analyzing data to inform business decisions. Both roles require strong analytical skills and programming knowledge, but Machine Learning Sports is specialized in the sports sector.

Infographic showing various Machine Learning Sports job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 94% Full Time, 4% Part Time, and 1% Temporary. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Swish Analytics

San Francisco, CA • Remote

$160K/yr

Full-time

Posted 29 days ago

Job description

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and enterprise clients.

The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. They can assist with optimizing the different aspects of the modeling process (Data Validation, Data Visualization, Data Stores & Structures, Feature Engineering, Model Training & Evaluation, Deployments) and improving a variety of Swish products. They will know when to “roll your own” and when to outsource a particular step in the modeling process. They will engineer custom solutions to solve complex data-related sports challenges across multiple leagues.

This position is 100% remote

Responsibilities:

  • Design, prototype, implement, evaluate, optimize systems to generate sports datasets and predictions with high accuracy and low latency.

  • Evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow.

  • Build, test, deploy and maintain production systems.

  • Work closely with DevOps and Data Engineering teams to assist with implementation, optimization and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages.

  • Support maintenance and optimization of cloud-native EDW and ETL solutions.

  • Maintain and promote best practices for software development, including deployment process, documentation, and coding standards.

  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.

  • Use extensive experience to build, test, debug, and deploy production-grade components.

  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.

  • Participate in development of database structures that fit into the overall architecture of Swish systems

Qualifications:

  • Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area

  • 5+ years of demonstrated experience developing and delivering clean and efficient production code to serve business needs

  • A proven background in quantitative analytics, trading, or engineering is required for this position

  • Demonstrated experience developing data science modeling systems and infrastructure at scale

  • Experience with Python and exposure to modern machine learning frameworks

  • Proficient in SQL; experience with MySQL

  • Background and/or interest in Rust preferred

  • Affinity for teamwork and collaboration with others to solve problems, share knowledge, and provide feedback

  • Strong communication skills when discussing technical concepts with technical and non-technical colleagues

Base salary: starting at $160,000 base plus bonus potential

Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks.