Top Machine Learning Jobs

As a Senior Machine Learning Engineer, you will define search metrics, optimize retrieval paths, and investigate search-quality issues to enhance operational excellence.

Lead innovative machine learning solutions for Chewy's advertising ecosystem, improving product relevance, ranking, and customer engagement through data-driven methodologies.

The Staff Machine Learning Engineer will develop ML models to enhance ad offerings, collaborate on product improvements, and publish research findings.

Develop and maintain ML solutions for AR/VR/MR products. Translate sensor capabilities into robust ML models, impacting defense technology.

The Senior Machine Learning Engineer will build AI-driven customer support products, collaborate cross-functionally, and maintain large-scale ML systems, leveraging modern techniques for real-world impact.

As a Staff Machine Learning Engineer, you will develop and maintain ML models for decision-making, optimize pipelines, and collaborate with a diverse engineering team.

The role focuses on developing data-driven models for optimizing catalyst materials via machine learning and quantum mechanical simulations, collaborating on catalysis research.

The Research Engineer will develop and benchmark ML algorithms, optimize transformer architectures for edge devices, and collaborate on research projects across teams.

As a Principal Quantitative Modeler, you will develop econometric and machine learning models for credit risk management, providing insights and solutions across Capital One's business. Responsibilities include partnering with different teams, applying quantitative methods, and delivering clear communication and documentation of modeling processes.

Lead centralized Machine Learning efforts at Affirm, managing model development lifecycles, fostering AI adoption, and overseeing a team of ML professionals to enhance business outcomes.

As a Machine Learning Engineer, you will develop AI/ML systems for robotics and manufacturing, adapt architectures for complex applications, and engage in research contributions.

As a Machine Learning Engineer, you'll build and deploy models for core products, apply ML techniques to solve problems, and collaborate on features.

Lead AI/ML engineering projects, develop predictive models, mentor team members, and collaborate on AI solutions for healthcare challenges.

Lead the design and deployment of machine learning models to detect fraud, collaborating with teams to optimize performance and effectiveness while integrating solutions into existing systems.

As an AI/ML Engineer Intern, contribute to the design, development, and deployment of AI/ML models, collaborate with teams, and optimize algorithms for business applications.

The ML Pricing Engineer will lead the development of AI-powered pricing platforms, focusing on scalable data infrastructure, feature engineering, and seamless ML integration, while collaborating with cross-functional teams.

As a Machine Learning Platform Engineer, you will partner with teams to establish data science environments, oversee analytic solutions, and lead complex projects while enhancing collaboration between technology and data science teams.

Assist in developing and deploying AI and ML features, collaborate with engineering teams, and align AI initiatives with the product vision.

The Senior Machine Learning Engineer will develop foundational models for recommendations, mentor engineers, and collaborate on improving user experiences with machine learning.

This role involves developing ML models for Hinge, collaborating with teams, deploying models, and optimizing systems for performance and cost.

The role involves designing ML models, research, improving ML capabilities, mentoring engineers, and managing data at scale utilizing cloud platforms.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

Conduct research and develop machine learning models for financial contexts, focusing on LLMs and deep learning applications. Collaborate to integrate solutions into trading strategies.

The intern will develop, deploy, and operate machine learning models, driving research projects to solve real-world problems and collaborate with senior engineers on identifying use cases for ML on blockchain.

Conduct research and develop machine learning models for finance, focusing on deep learning and large language models, optimizing them for performance, and collaborating with teams to integrate ML solutions.