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Sports Analytics Machine Learning Jobs in Berkeley, CA

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 ...

Articul8

Machine Learning Engineer

Dublin, CA · On-site

$90 - $130/hr

... and data analysis. You will own all work related to acquiring high-quality data to power the ... Experience in machine learning projects in text or vision, e.g., has trained machine learning ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

Create analytics environments and resources in the cloud or on premise, spanning data engineering ... Experience applying Machine learning methods (including 3D graph/point cloud deep learning methods ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site

Create analytics environments and resources in the cloud or on premise, spanning data engineering ... Experience applying Machine learning methods (including 3D graph/point cloud deep learning methods ...

Articul8

Machine Learning Engineer

Dublin, CA · On-site

... and data analysis. You will own all work related to acquiring high-quality data to power the ... Experience in machine learning projects in text or vision, e.g., has trained machine learning ...

Umba

Machine Learning Lead

San Francisco, CA · On-site

Your primary focus will be in applying data mining techniques, doing statistical analysis, and ... We train and deploy new machine learning models regularly and subscribe to data driven decision ...

Walmart

(USA) Staff, Machine Learning Engineer

Hayward, CA · On-site

$169K - $338K/yr

Collaborating with Product, Business, Data, and Platform groups, they apply expertise in predictive analytics, machine learning, and data visualization. Key responsibilities include identifying data ...

Eve

Machine Learning Engineer

San Francisco, CA

Build AI systems that understand, analyze, and reason across complex legal tasks and queries ... Machine Learning Engineer who enjoys building real systems people depend on. You'll likely have ...

Capable

Machine Learning Engineer

San Francisco, CA · On-site

$150K - $240K/yr

About the Role You will build machine-learning systems that remove real bottlenecks from drug ... Develop candidate-analysis workflows that may include molecular dynamics, post-training, probing ...

New

Capable

Machine Learning Engineer

San Francisco, CA · On-site

$150 - $230/hr

About the Role You will build machine-learning systems that remove real bottlenecks from drug ... Develop candidate-analysis workflows that may include molecular dynamics, post-training, probing ...

New

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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 are popular job titles related to Sports Analytics Machine Learning jobs in Berkeley, CA?

For Sports Analytics Machine Learning jobs in Berkeley, CA, the most frequently searched job titles are:

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

Skild AI

San Mateo, CA

Full-time

Re-posted 29 days ago

Job description

Position Overview

We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments. This will require close collaboration with our robotics, research, and engineering team. Your work will directly impact the development of intelligent, adaptable robots capable of learning and performing complex tasks autonomously.

Responsibilities
  • Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.
  • Design and conduct experiments to train RL models and conduct real-world tests.
  • Collaborate closely with researchers to explore novel methods of scaling up reinforcement learning model training.
  • Communicate effectively with inference, application, and deployment engineers to integrate RL models into robotic systems and iterate on methods to enable robust deployment.
  • Analyze and interpret experimental results, iterating on model design to achieve desired performance.
  • Stay up-to-date with the latest research and advancements in reinforcement learning.
Preferred Qualifications
  • BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
  • Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
  • Deep understanding and practical experience with various reinforcement learning algorithms and techniques (model-free, model-based, multi-task, hierarchical, multi-agent, etc.).
  • Strong background in algorithms, data structures, and software engineering principles.
  • Experience with physics simulation engines and tools for training RL.
  • Deep understanding of state-of-the-art machine learning techniques and models.
  • Extensive industry experience with reinforcement learning and robotic systems.

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