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Sports Analytics Machine Learning Jobs in Berkeley, CA

Winaxis

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only ... Familiarity with multi-modal data integration and analysis. Strong problem-solving skills and the ...

MM International

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA once the documents are verified, a Codility ... Familiarity with multi-modal data integration and analysis. * Strong problem-solving skills and the ...

Hive

Machine Learning Manager

San Francisco, CA · On-site

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Hive

Machine Learning Engineer

San Francisco, CA

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ... and analyzing the results in the wild in order to continuously update and improve accuracy and ...

Hive

Machine Learning Manager

San Francisco, CA · On-site

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ... and analyzing the results in the wild in order to continuously update and improve accuracy and ...

Skild AI

Machine Learning Engineer

San Mateo, CA · On-site

$100K - $300K/yr

Analyze and interpret experimental results, iterating on model design to achieve desired ... Deep understanding of state-of-the-art machine learning techniques and models. * Extensive industry ...

AllSTEM Connections

Machine Learning Engineer

San Francisco, CA · On-site

$118K - $129K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

Machine Learning Engineer Role Overview We are seeking an experienced and driven Machine Learning ... analysis and intelligent automation. • Data Integration: Utilize Python, R, and advanced SQL ...

Unitytech

Machine Learning Engineer

San Francisco, CA · On-site +1

$117K - $152K/yr

  • Medical

  • Life

  • Retirement

  • PTO

Our systems operate at scale across batch and streaming data, supporting analytics, product intelligence, machine learning pipelines, and business operations. As data volume and complexity grow, our ...

Skild AI

Machine Learning Engineer

San Mateo, CA

Analyze and interpret experimental results, iterating on model design to achieve desired ... Deep understanding of state-of-the-art machine learning techniques and models. * Extensive industry ...

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All JobsSports Analytics Machine Learning JobsSports Analytics Machine Learning Jobs in Berkeley, CA

Sports Analytics Machine Learning information

What is sports analytics machine learning?

Sports analytics machine learning is the application of data science and machine learning techniques to analyze sports data, such as player statistics, game outcomes, and biometric information. Professionals in this field develop models to identify patterns, predict player performance, optimize team strategies, and gain competitive advantages. This work involves collecting large datasets, cleaning and processing data, and using algorithms to extract actionable insights that can benefit teams, coaches, and athletes. Sports analytics with machine learning is increasingly used in professional sports to inform decisions about training, recruitment, and game tactics.

How do sports analytics machine learning professionals typically collaborate with coaches and athletes to impact game strategy?

Sports Analytics Machine Learning professionals often work closely with coaches and athletes by translating complex data insights into practical recommendations. They attend strategy meetings, present findings through visualizations, and help interpret trends that can influence training, player selection, and in-game tactics. Effective communication is key, as these professionals must bridge the gap between technical analyses and real-world sports applications. This collaborative environment not only enhances team performance but also provides opportunities to see the direct impact of your work on the field.

What are the key skills and qualifications needed to thrive as a sports analytics machine learning specialist, and why are they important?

To thrive as a Sports Analytics Machine Learning Specialist, you need a strong background in statistics, data analysis, programming (typically in Python or R), and an understanding of machine learning algorithms, often supported by a degree in data science, statistics, or a related field. Familiarity with data visualization tools, sports databases, and machine learning frameworks like TensorFlow or scikit-learn is essential, along with experience using SQL and data pipelines. Strong problem-solving, communication, and collaboration skills help translate complex data findings into actionable insights for coaches, players, and stakeholders. These skills are crucial for extracting meaningful patterns from vast sports datasets and driving performance improvements or strategic decisions within sports organizations.

What job categories do people searching Sports Analytics Machine Learning jobs in Berkeley, CA look for?

The top searched job categories for Sports Analytics Machine Learning jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Sports Analytics Machine Learning jobs?

Cities near Berkeley, CA with the most Sports Analytics Machine Learning job openings:

Sports Analytics Machine Learning jobs near you
Infographic showing various Sports Analytics Machine Learning job openings in Berkeley, CA as of August 2026, with employment types broken down into 82% Full Time, and 18% Part Time. Highlights an 100% In-person job distribution.

Machine Learning Engineer

Winaxis

Fremont, CA • On-site

Contractor

Re-posted 5 hours ago

Job description

Title: Machine Learning Engineer

Location: Fremont, CA (Local) Onsite interview

Duration: 12+ Mos  

H1B

Only h1 candidate

About the Role:

Our direct client is hiring a Machine Learning Engineer for their software machine learning and computer vision team to design, develop, and implement critical machine learning models supporting factory and warehouse operations. You will transform ambiguous problem statements into robust end-to-end solutions using a variety of machine learning techniques and tools, including supervised learning, convolutional neural networks, and modern frameworks such as PyTorch and Pandas.

You will collaborate closely with partners in production, process, controls, and quality to deliver solutions for the most challenging problems in our operations. Your work will involve evaluating and deploying models in production environments, ensuring rapid and reliable alerting systems, and addressing operational issues as they arise. You must be adept at handling diverse, heterogeneous datasets that span multiple modalities, including images, multi-spectral sensor outputs, voice, text, and tabular data.

Responsibilities

Design, develop, and deploy machine learning models for factory and warehouse environments.

Collaborate with cross-functional teams to identify, define, and solve high-impact operational challenges.

Build and maintain end-to-end machine learning pipelines, from data collection and preprocessing to model deployment and monitoring.

Evaluate and compare models using statistical methods to ensure optimal performance and feasibility.

Ensure robust alerting and monitoring systems are in place for deployed models to address issues rapidly.

Work with diverse datasets, integrating multiple data types such as images, sensor data, voice, text, and tabular information.

Write clean, modular, and sustainable code to translate research ideas into production-ready solutions.

Minimum Requirements

In-depth knowledge of Python for high-performance, data-intensive applications.

Proficiency with at least one modern deep learning framework (e.g., PyTorch, Jax, TensorFlow).

Expertise in one or more of the following areas: computer vision, large language models, recommender systems, or operations research.

Foundational knowledge of statistics for model comparison and performance assessment.

Real-world experience deploying and maintaining machine learning solutions in production environments.

Passion for clean, sustainable, and modular code to bring research concepts to practical implementation.

Preferred Qualifications

Experience working in manufacturing, industrial automation, or warehouse environments.

Familiarity with multi-modal data integration and analysis.

Strong problem-solving skills and the ability to thrive in ambiguous, fast-paced settings.

Excellent communication skills for cross-functional teamwork.