Top Machine Learning Jobs

Lead the development of pricing algorithms for vehicle valuation at CarMax, managing a team of data scientists to implement strategies and maintain optimal pricing models.

The role involves developing machine learning models for cash forecasting, collaborating with stakeholders, and owning the ML lifecycle from development to deployment.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Staff Machine Learning Engineer will design backend software components, ensuring platform performance and reliability, while integrating GPU hardware and leading large initiatives within GM's AI ecosystem.

The Machine Learning Engineer will design, build, and deploy ML applications at scale, collaborating with cross-functional teams and applying best practices in ML engineering and cloud technologies.

Lead a team of Machine Learning Engineers in designing, building, and implementing ML applications, focusing on data-intensive solutions and infrastructure decisions, while promoting best practices in AI.

The role involves developing ML models, conducting experiments, and optimizing car assignments to improve Waymo's Marketplace efficiency.

Develop machine learning models and optimize pricing algorithms to enhance Lyft's market dynamics, collaborating with cross-functional teams on real-world business problems.

As an Applied Scientist at Lyft, you will develop ML and optimization models for dynamic pricing, collaborate across teams, and implement algorithms to enhance rider experience.

The Director of Machine Learning Engineering is responsible for leading AI strategy, overseeing ML solutions, driving innovation, building teams, and ensuring operational excellence in ML systems.

Lead and build a Machine Learning team, driving strategy and execution across product areas like Document Generation and Voice Agents while collaborating with Product and Engineering.

Develop and operationalize machine learning models for lab automation, leveraging multimodal data and ensuring reliable predictive capabilities in drug discovery processes.

The Research Engineer/Scientist will advance decision-making in critical industries using optimization and machine learning, collaborating with product managers and engineers.

As a Software Engineering Intern, you'll develop features for user-facing products, work on API platforms, and design data pipelines while gaining hands-on experience in AI technologies.

Design, build, and deploy AI features for claim synthesis; implement machine learning solutions and improve model performance through collaboration and evaluation.

Conduct model development and implementation for risk models, support sales initiatives, analyze transaction data with big data technologies, and promote analytics education at Visa.

Lead machine learning initiatives, oversee product development, improve execution pace, enhance team reliability, and foster team growth at Hightouch.

Lead a team of engineers to enhance AI-powered search relevance through machine learning. Oversee model development, project management, and team growth while collaborating across departments.

As a Machine Learning Engineer in Fraud Risk, you'll build and maintain ML systems for fraud detection and anomaly analysis, ensuring robust performance and real-time decision making.

This role involves building and optimizing ML systems and frameworks, collaborating with teams to enhance research and development in ML models.

Lead the design, development, and deployment of machine learning models, collaborating with teams and mentoring engineers. Focus on scalable ML workflows.

Lead the design and implementation of advanced ML models for autonomous driving, collaborating with teams, mentoring engineers, and driving technical initiatives.

The Principal ML Engineer at Agero will develop and productionize a Dispatch System using ML models, optimize decision-making processes, and lead a team to improve operational performance.

As Machine Learning Product Director, define ML strategy and manage product development for Attrition Risk Insights, enhancing customer engagement through predictive modeling.

As a Principal Machine Learning Engineer, you will develop multimodal AI experiences, design agent interactions, and lead cross-team initiatives while ensuring AI safety and reliability.