Top Machine Learning Engineer Jobs

The Machine Learning Engineer will build and deploy ML models, applying modern techniques to solve problems and collaborate with teams on ML-driven features.

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

As a Machine Learning Engineer, you will enhance internal libraries for deep learning, collaborate with researchers, and optimize workflows for cost savings.

The Staff Machine Learning Engineer designs and implements infrastructure for AI workloads, collaborates with teams, mentors, and ensures code quality, focusing on machine learning and distributed systems.

As a Staff Machine Learning Engineer, you will design and implement infrastructure for AI workloads, collaborate on GPU cluster performance, and write scalable code while mentoring colleagues.

As a Machine Learning Engineer II, you will design, implement, and maintain machine learning models, optimize workflows, and collaborate with cross-functional teams to deploy ML systems.

The role involves designing and deploying machine learning systems for a search platform, focusing on ranking and retrieval while collaborating with cross-functional teams.

The Principal Machine Learning Engineer shapes the machine learning strategy and architecture, leads initiatives, mentors engineers, and influences technical decisions at SharkNinja.

Design and deploy scalable machine learning models, analyze datasets, collaborate on ML standards, and communicate solutions to stakeholders.

The role involves developing AI/ML models using Generative AI technologies, deploying solutions, collaborating with Pharmacy teams, and optimizing performance.

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.

Design and maintain ML pipelines and data pipelines, optimize fraud detection models, collaborate with teams, and ensure data quality for high-scale applications.

As a Staff Machine Learning Engineer, you will design and develop ML systems to combat fraud by building data pipelines, integrating data sources, and ensuring high-quality model performance while collaborating with teams.

Design and maintain ML pipelines, build data ingestion tools, collaborate with data teams, ensure data quality, and solve technical challenges in a fast-paced environment.

As a Staff Machine Learning Engineer, you will design and develop machine learning systems to prevent fraud, ensuring data quality and integrating diverse data sources while collaborating with cross-functional teams.

Design and develop NLP, ML, and AI products for healthcare, managing model lifecycles, conducting proofs-of-concept, and optimizing large-scale systems.

As a Machine Learning Engineer in the Risk AI/ML team at Coinbase, you'll develop, enhance, and deploy ML models to prevent fraud and improve security for users. This role involves end-to-end model ownership, responding to threats, and collaborating with various teams to create automated defenses.

As a Staff Machine Learning Engineer, you will set the technical direction for the Ad Ranking team, design and deploy machine learning solutions, and mentor engineers while driving large cross-team initiatives.

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.

As a Machine Learning Engineer, you will design algorithms, maintain data pipelines, collaborate on software deployment, and ensure the scalability of ML systems.

As a Machine Learning Engineer, you will design and optimize algorithms, manage ML data pipelines, and ensure system scalability while collaborating with teams to enhance software deployment.

As a Machine Learning Engineer, you'll enhance ML productivity, improve model deployment, and implement algorithms for credit decisioning systems.

The Machine Learning Engineer will maintain and expand the ML platform, working on scalable systems, model serving, and collaborating closely with cross-functional teams.

Lead complex AI/ML projects from conception to production, mentoring teams, performing data analysis, and establishing AI/ML best practices in healthcare.