Machine Learning Methods jobs in United States Skill: Machine Learning Methods Machine Learning Engineer, Wallet Intelligence and Machine Learning
Apple · Austin, US+1 more On-site
Machine Learning Engineer, Wallet Intelligence and Machine Learning
Apple · Austin, US+1 more On-site · Full-time
Senior AI/ML Scientist
Blue Cross and Blue Shield of North Carolina · US· Hybrid · Full-time · Senior
UX Designer III
Pride Global · Remote, US· Remote · Contract · Senior
Director, Model Risk — AI & Fraud
OKX · New York, US+1 more · Senior
+10K new in the last hour
Apple · Posted Jul 17, 2026
Develop and launch on-device machine learning technologies to protect users from fraud while preserving privacy.
Austin, Texas, United States New York City, New York, United States Build analytical solutions for fraud prevention Design models that run in real time on-device Collaborate with engineering, security, program management, and business partners Own problem areas and develop system-wide understanding of model integration Nice to have: on-device deployment Nice to have: model compression Nice to have: inference budgets optimization Nice to have: privacy-preserving machine learning Nice to have: fraud detection Apple · Posted Jul 17, 2026
Develop and launch on-device machine learning technologies to keep users safe from fraud while maintaining privacy, designing models that work within resource constraints like model size and inference budgets.
Austin, Texas, United States New York City, New York, United States Develop and launch on-device technologies that keep users safe Work closely with engineering, security, program management, and business partners Build models that run in real time and in the background on the device Anticipate fraud rather than react to patterns Take ownership of a problem area Nice to have: on-device deployment Nice to have: model compression Nice to have: optimizing for inference budgets Nice to have: Spark Nice to have: Ray Blue Cross and Blue Shield of North Carolina · Posted Jun 15, 2026
Senior AI/ML scientist to develop predictive, prescriptive, and generative AI solutions for organizational decision-making
$143,616.00 - $229,786.00
Own delivery of large and/or complex machine learning, deep learning, and generative AI systems with self-learning capabilities Design, implement, and evaluate AI systems for production environments Apply prescriptive analytics techniques such as optimization, recommendation systems, and reinforcement learning Lead development and testing of ML algorithms, design & conduct experiments, collect and analyze data, and optimize performance Benchmark against existing machine learning methods and analyze results Bachelor's degree or advanced degree (where required) Pride Global · Posted Nov 3, 2026
Lead the design and development of conversational AI experiences, translating business requirements into scalable AI solutions.
Research and recommend industry best practices and emerging approaches in Conversational AI. Apply NLP techniques to transform natural language data for classification algorithms. Collaborate with engineers and applied research scientists to develop efficient, scalable AI solutions. Define technical direction and architecture for conversational assistants. Translate high-level business requirements into detailed system-level and functional requirements. Bachelor's degree or equivalent practical experience. Master's degree in Computer Science, Computational Linguistics, Engineering, Informatics, or a related field preferred. Nice to have: Salesforce experience Nice to have: workforce optimization projects Nice to have: leading a cross-functional pod or project Lead the independent validation of fraud and AI models across OKX products, establishing and maintaining a robust model risk framework.
New York, New York, United States San Jose, California, United States The salary range for this position is $200,000 - $300,000
Establish and own the independent validation framework for fraud models and AI-enabled decision systems Assess model conceptual soundness, intended use, assumptions, and limitations Personally execute end-to-end model validations, including data analysis and code review Assess AI/ML and generative AI applications for robustness, reliability, explainability, and human oversight Perform ongoing monitoring and periodic revalidation of models Master’s or Ph.D. in a quantitative field such as Statistics, Mathematics, Computer Science, or equivalent
Annual Incentive Bonus 401(k) with employer match Paid Time Off (PTO) Competitive health benefits and wellness programs
comprehensive healthcare coverage (medical, dental, vision plans) supplemental coverage (accident insurance, critical illness insurance, hospital indemnity) 401(k)-retirement savings life & disability insurance employee assistance program
Nice to have: validation frameworks
Nice to have: prompt engineering
Nice to have: evaluation harnesses
Nice to have: fine-tuning assessment Wellness and meal allowances Comprehensive healthcare schemes Team building programs and company events
Machine Learning Engineer, Wallet Intelligence and Machine LearningNewApple · Austin, US+1 more
Director, Model Risk — AI & FraudOKX · New York, US+1 more