AI Jobs

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

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

Benefits:

• Equity awarded at the 6-month mark

• Public transit pass

• Competitive Pay

• Health insurance

• Paid vacation and sick leave

Education Requirements:

• Master/Phd Required

Experience Requirements:

• Data science and technical experience

• Successful customer data implementation experience

• Demonstrable leadership skills

• Successfully partnered with Sales Leaders

Other Requirements:

• Build strong rapport and establish trust and credibility

• Strong analytical capabilities for advanced problem-solving

• Excellent written and oral communication skills

• Comfortable working in a high-growth, constantly changing environment

• Polished and professional business acumen

Responsibilities:

• Own Data Science processes end-to-end

• Collaborate with the Product and Engineering team

• Collaborate with product, engineering, and customers to standardize process

• Designing and building data pipelines infrastructure

• Take a leading part in building our research program

Benefits:

• 100% employer-paid health, vision, and dental insurance

• Retirement plans (401k)

• Disability insurance

• Employee assistance programs

• Competitive compensation

Education Requirements:

• PhD or Master’s in ML, CV, NLP, or related field

Experience Requirements:

• 5+ years of experience working on vision or VLMs

• Proven experience applying ML to healthcare documents or medical imaging

Other Requirements:

• Hands-on with PyTorch, HuggingFace, OpenCLIP

• Deep understanding of HIPAA and PHI protection

• Comfortable with RAG pipelines

Responsibilities:

• Research and build state-of-the-art VLM pipelines for medical documents

• Fine-tune or adapt models like BLIP-2, LLaVA, GLaMM

• Develop multimodal grounding strategies for RAG and Agent workflows

• Evaluate models for factuality, safety, and explainability

• Collaborate with product engineers to deploy models at scale

Benefits:

• 100% employer-paid health, vision, and dental insurance

• Retirement plans (401k)

• Disability insurance

• Employee assistance programs

• Competitive compensation

Education Requirements:

• Bachelor’s degree in a healthcare-related field

Experience Requirements:

• 5+ Years of experience in healthcare data/research

Other Requirements:

• Knowledge of clinical coding systems (ICD-10, CPT, SNOMED CT)

• Familiarity with EMR systems

• Certification in medical coding (CPC, CCS) preferred

Responsibilities:

• Provide clinical guidance for AI co-pilots

• Develop annotation guidelines for healthcare data

• Review and annotate clinical documents like EMRs and medical charts

• Tag data using standard clinical terminologies

• Perform quality control and inter-annotator agreement checks

Experience Requirements:

• 5-8yrs

Other Requirements:

• Data Science team

• No. of Openings : 1

Benefits:

• Medical, dental, vision

• 401(k) with match

• Generous PTO

• Flexible scheduling

• Company-provided home-office equipment

Education Requirements:

• PhD/PsyD (or equivalent) in Clinical Psychology or a closely related field

Experience Requirements:

• 4-5 years work experience

• ≥ 3 years post-doctoral experience conducting clinical outcome assessments (ClinROs) in trials

Other Requirements:

• Formal training in mood-disorder interviews (HAM-D, MADRS, etc.)

• Professional video presence and reliable high-speed internet

• Comfort working across U.S. time zones

• Licensure not required for this research-only role

Responsibilities:

• Administer & score clinician-rated instruments (HAM-D, MADRS, etc.) via secure video

• Document in 21 CFR Part 11–compliant platforms

• Audit peer assessments and resolve scoring discrepancies

• Train and mentor new raters and co-lead calibration meetings

• Collaborate with product & data-science teams to pilot AI-assisted assessments