Top Machine Learning Jobs

The role involves designing, developing, and deploying machine learning models and systems, collaborating with engineers and product teams to ensure reliable and scalable solutions while mentoring junior engineers.

Design and deploy production-grade ML systems, integrate models into software pipelines, and develop features leveraging ML for optimization and prediction problems.

Lead the development of production-grade ML systems, aligning technical roadmaps with company priorities, mentoring ML engineers, and ensuring ethical use of ML/AI.

The role involves developing an AI agent platform, building ML models, and enhancing user experiences with advanced algorithms. Collaboration and fast-paced execution are key.

As a Senior Principal Machine Learning Engineer, you'll lead technical projects, mentor teams, and implement ML systems, focusing on AI in AEC solutions.

The Industry Architect for Advertising & Media at Snowflake drives technical transformation in media measurement and marketing science, partnering with global brands and agencies to innovate data architectures and optimize media investments using AI and privacy-safe technologies.

Lead the Applied Machine Learning team at ExtraHop to develop systems for behavioral detection in network security. Manage model design, evaluation, and operationalization while maintaining experimental rigor and collaborating with product teams.

Lead the development of production-grade machine learning systems, build ML pipelines, and optimize models for deployment and performance.

Join Capsule as an AI Engineer to develop ML models for video editing. Responsibilities include researching ML techniques, collaborating on feature development, and optimizing model performance.

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.