AI Jobs

Education Requirements:

• Degree in Industrial Engineering, Statistics, Economics

Experience Requirements:

• 5+ years as a data or product analyst

• Proficiency using SQL and Excel

• Experience with product analytics methodologies

• Experience with Tableau or Looker

Other Requirements:

• Fluency in common statistical analysis methods

• Strategic thinking

• Self-motivation

Responsibilities:

• Present data-driven insights to leadership

• Build business cases for new functionality

• Lead deep-dive strategy analysis

• Design and maintain ongoing dashboards

• Ensure right data is generated and collected

Benefits:

• Mentorship from world-class researchers

• Hybrid working (3 days in-office expectation)

• Free team lunches (Tue-Thu)

• Optional social activities

• Annual international offsite

Education Requirements:

• Strong background in machine learning, LLMs, NLP, or related fields

Experience Requirements:

• Experience with research methodologies and experimental design

• Proficiency in Python

Other Requirements:

• Must have the right to work in the UK

• Ability to work from 08/06/2026 to 28/08/2026

• No visa sponsorship available

Responsibilities:

• Conduct original research in AI/NLP

• Develop and implement novel algorithms and models

• Analyse experimental results

• Contribute to research publications

• Present findings to the research team

Benefits:

• Health coverage

• Retirement plans

• Unlimited paid time off

• Flexible and remote work options

• Learning and development stipends

Education Requirements:

• Master's or PhD in Statistics, Data Science, Computer Science, or related quantitative field

Experience Requirements:

• Strong to extensive experience working with sports data and analytics

• Solid to deep foundation in statistical modeling, machine learning, and predictive analytics

• Proficiency in building data science solutions from concept to deployment

• Experience working with large, complex datasets and database systems

• Advanced proficiency in cloud-based computing platforms

Other Requirements:

• Curiosity and passion for sports

• Collaborative mindset

• Aligned with core values: honesty, humility, hard work, commitment, innovation, and exceptionalism

Responsibilities:

• Build end-to-end data science solutions and predictive models

• Design and implement sports analytics tools for athlete evaluation

• Lead the design of complex, high-impact data science tools

• Provide technical mentorship and guidance to data scientists

• Engage with sports operations teams to translate analytics into actionable insights

Education Requirements:

• Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area

Experience Requirements:

• Demonstrated experience developing models at production scale for hockey or sports betting for 2+ years

• Expertise in Probability Theory, Machine Learning, and Inferential Statistics

• 5+ years experience delivering effective machine learning/statistical models in sports or betting

• Experience with relational SQL & Python

• Experience with source control tools such as GitHub

Other Requirements:

• Excellent communication skills

• Proven track record of strong leadership skills

• Experience working in AWS environments

Responsibilities:

• Ideate and develop machine learning and statistical models

• Develop contextualized feature sets using sports domain knowledge

• Partner with data engineering and product teams to deploy models

• Improve model performance using offline and online experimentation

• Document modeling work and present to stakeholders

Benefits:

• Paid internship

Education Requirements:

• Undergraduate degree (senior status minimum) in related field

Experience Requirements:

• Internship and/or part-time experience with other sports teams preferred

Other Requirements:

• Excellent statistical and analytical skills

• Experience using Tableau is preferred

• Ability to work non-traditional hours

• Willingness to lift and carry 25-50 pounds

Responsibilities:

• Development and maintenance of key reports and visualizations

• Perform exploratory data analysis to identify trends and patterns

• Provide recommendations addressing business goals using quantitative and qualitative data

• Support ad-hoc data analysis requests from different departments

• Assist in development of CRM features

Education Requirements:

• Bachelor’s degree in Performance Analysis, Sport Science, Data Science or related field (or currently pursuing)

Experience Requirements:

• Experience as a video or data analyst working with coaches

• Experience filming and coding soccer training sessions or matches

• Working knowledge of Hudl Sportscode or similar video analysis platforms

• Strong understanding of soccer tactics and principles of play

Other Requirements:

• Must reside within Washington state upon date of hire

• Must be eligible to work in the US without sponsorship

• Ability to operate video cameras; drone experience preferred

• Proficiency in Microsoft Office

Responsibilities:

• Deliver video and data support aligned with team standards

• Record, capture, and code First Team training and matches

• Prepare and edit clips to support player development

• Contribute to the opponent scouting process

• Support game day setup and live analysis workflows

Education Requirements:

• Currently pursuing an undergraduate or graduate degree in economics, statistics, mathematics, computer science, data science, or related field

Experience Requirements:

• Foundational programming experience with R, Python, or similar

• Familiarity with SQL

• Basic proficiency with Microsoft Office

• Exposure to data visualization tools preferred

Other Requirements:

• Interest in sports business and fan engagement

• Strong analytical thinking and problem-solving abilities

• Ability to manage time effectively and meet deadlines

Responsibilities:

• Aggregate, clean, and transform data for analysis

• Assist in building reports and dashboards using Tableau

• Support ad-hoc analysis requests across departments

• Assist with CRM data quality initiatives in Salesforce

• Contribute to consumer insights projects

Benefits:

• Competitive Salaries

• Company Stock Options

• Health, Vision & Dental Coverage

• Learning & Development

• Flexible Work Hours

Benefits:

• Diverse and inclusive workplace

• Equal opportunity employer

Experience Requirements:

• 1+ years of experience in data science

Other Requirements:

• Proficiency in Python (ML libraries) and SQL

• Hands-on experience with ETL processes and large datasets

• Knowledge of frameworks like LangChain or Langraph

• Ability to design AI agents using RAG

• Familiarity with AWS or major cloud platforms

Responsibilities:

• Design, develop, and deploy data science solutions

• Translate business challenges into scalable data products

• Develop, evaluate, and deploy machine learning models

• Explore and integrate new technologies like LLMs and AI agents

• Ensure data quality and integrity across multiple sources

Education Requirements:

• BS/MS in Engineering, Science, or a related field

• MS in Computer Science, Data Science, or related field

Experience Requirements:

• 3+ years of experience leading AI or data science projects in the semiconductor industry or another manufacturing field

Other Requirements:

• Proficiency in data science tools: Python and SQL

• Ability to work independently and as part of a team

• Travel domestically to customer sites as needed (up to 20% of working hours)

• Fluency in Korean

• Fluency in English

Responsibilities:

• Design and implement customized AI solutions for manufacturing

• Analyze manufacturing data to uncover opportunities and develop AI models

• Collaborate with customers to understand their requirements and deliver clear, data-driven solutions

• Work closely with our internal teams to ensure solutions are feasible, scalable, and aligned with product strategy

• Present findings to both technical and non-technical stakeholders

Education Requirements:

• Ph.D. or Master’s degree in Computer Science, Machine Learning, Statistics, or a related field.

Experience Requirements:

• 3+ years of hands-on experience in deep learning, with a strong focus on sequence modeling and time-series forecasting.

• Practical experience deploying ML models in production environments, with knowledge of MLOps best practices.

Other Requirements:

• In-depth expertise in Transformer architectures and their applications beyond natural language processing.

• Proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX.

• Solid mathematical foundation in statistics, optimization, and signal processing.

• Strong publication track record in top-tier ML/AI conferences (e.g., NeurIPS, ICML, ICLR).

Responsibilities:

• Design and implement Transformer-based architectures for time-series prediction and sequence modeling

• Drive the full machine learning lifecycle—from exploratory data analysis to model deployment

• Conduct rigorous benchmarking, ablation studies, and performance optimization

• Collaborate closely with data scientists, engineers, and product managers

• Partner with software engineers to scale and productize ML algorithms

Other Requirements:

• Exceptional abilities and the drive to make an impact

Responsibilities:

• Build Quantum-Native AI to simulate complex systems

• Tackle the intractability of complex chaos

• Bridge causal gaps in Quantum Foundations: Adiabatic Annealing, Control Theory, & Error Correction

• Develop Quantum-ML Hybrids and High-Performance Research Engineering

• Research Neural Topology, Theoretical Neuroscience, and Neuromorphic Engineering

Other Requirements:

• Exceptional abilities and the drive to make an impact

Responsibilities:

• Build Quantum-Native AI to simulate complex systems

• Tackle the intractability of complex chaos

• Bridge causal gaps in Quantum Foundations: Adiabatic Annealing, Control Theory, & Error Correction

• Develop Quantum-ML Hybrids and High-Performance Research Engineering

• Research Neural Topology, Theoretical Neuroscience, and Neuromorphic Engineering

Other Requirements:

• Exceptional abilities and the drive to make an impact

Responsibilities:

• Build Quantum-Native AI to simulate complex systems

• Tackle the intractability of complex chaos

• Bridge causal gaps in Quantum Foundations: Adiabatic Annealing, Control Theory, & Error Correction

• Develop Quantum-ML Hybrids and High-Performance Research Engineering

• Research Neural Topology, Theoretical Neuroscience, and Neuromorphic Engineering

Other Requirements:

• Exceptional abilities and the drive to make an impact

Responsibilities:

• Build Quantum-Native AI to simulate complex systems

• Tackle the intractability of complex chaos

• Bridge causal gaps in Quantum Foundations: Adiabatic Annealing, Control Theory, & Error Correction

• Develop Quantum-ML Hybrids and High-Performance Research Engineering

• Research Neural Topology, Theoretical Neuroscience, and Neuromorphic Engineering

Other Requirements:

• Exceptional abilities and the drive to make an impact

Responsibilities:

• Build Quantum-Native AI to simulate complex systems

• Tackle the intractability of complex chaos

• Bridge causal gaps in Quantum Foundations: Adiabatic Annealing, Control Theory, & Error Correction

• Develop Quantum-ML Hybrids and High-Performance Research Engineering

• Research Neural Topology, Theoretical Neuroscience, and Neuromorphic Engineering

Other Requirements:

• Exceptional abilities and the drive to make an impact

Responsibilities:

• Build Quantum-Native AI to simulate complex systems

• Tackle the intractability of complex chaos

• Bridge causal gaps in Quantum Foundations: Adiabatic Annealing, Control Theory, & Error Correction

• Develop Quantum-ML Hybrids and High-Performance Research Engineering

• Research Neural Topology, Theoretical Neuroscience, and Neuromorphic Engineering

Other Requirements:

• Exceptional abilities and the drive to make an impact

Responsibilities:

• Advance the next generation of neural network architectures

• Develop Large Language Models (LLMs) and AI agents

• Directly impact enterprise AI applications and real-world solutions

• Drive immediate value with classical AI approaches

Other Requirements:

• Exceptional abilities and the drive to make an impact

Responsibilities:

• Advance the next generation of neural network architectures

• Develop Large Language Models (LLMs) and AI agents

• Directly impact enterprise AI applications and real-world solutions

• Drive immediate value with classical AI approaches

Other Requirements:

• Exceptional abilities and the drive to make an impact

Responsibilities:

• Advance the next generation of neural network architectures

• Develop Large Language Models (LLMs) and AI agents

• Directly impact enterprise AI applications and real-world solutions

• Drive immediate value with classical AI approaches