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Sports Analytics Machine Learning Jobs in Milpitas, CA

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

... analysis and data visualization techniques • Understanding of deep learning architectures and algorithms • Excellent problem-solving and critical-thinking skills Company : We are a leading ...

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

Contribute to the development and application of advanced analysis methodologies; analyze data ... Master's degree in Machine Learning, Computational Biology, Statistics, Computer Science ...

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

$9.7K/wk

Contribute to the development and application of advanced analysis methodologies; analyze data ... Master's degree in Machine Learning, Computational Biology, Statistics, Computer Science ...

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 ...

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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 Milpitas, CA look for?

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

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

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

Sports Analytics Machine Learning jobs near you

Machine Learning Engineer - ML Agents, Planning

Jobtailor

Foster City, CA • On-site

$180 - $250/hr

Other

Posted 9 days ago

Job description

  • You will develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for human-like agents.
  • You will work on novel techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort and realism.
  • You will contribute to our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field
  • You will develop metrics and tools to analyze errors and understand improvements of our systems
  • You will collaborate with engineers on Perception, Planning, Simulation, and Validation to solve the overall Autonomous Driving problem.
Requirements
  • PhD degree in computer science or related field or master's degree and 5+ years of professional experience in a relevant field.
  • Experience in Planning and / or Prediction using Reinforcement Learning techniques
  • Experience with training and deploying transformer-based model architectures
  • Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
  • Fluency in Python with a basic understanding of C++
Core Competencies

Expertise in developing deep learning models for autonomous driving, with a focus on imitation learning and reinforcement learning. Proficient in creating and analyzing machine learning pipelines, metrics, and tools to enhance system performance and safety.

Highest-signal resume keywords
  • PhD In Computer Science
  • Reinforcement Learning Techniques
  • Transformer-Based Model Architectures
  • Production Machine Learning Pipelines
  • Fluency In Python
ATS Optimization Keywords Hard Skills
  • Deep Learning Models
  • Imitation Learning
  • Reinforcement Learning
  • Planning
  • Prediction
  • Metrics Development
  • Error Analysis
  • Dataset Creation
  • Training Frameworks
  • Model Deployment
Industry Keywords
  • Autonomous Driving
  • Safety
  • Comfort
  • Realism
  • Collaboration
Tools & Technologies
  • Machine Learning Infrastructure
  • Python
  • C++
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