Top Machine Learning Engineer Jobs

Build scalable ML infrastructure for Large Language Models (LLMs), automate workflows, and collaborate with cross-functional teams to enhance AI product offerings.

The role involves building and optimizing ML infrastructure for large language models, collaborating with cross-functional teams, and driving ML best practices.

The Lead AI/ML Engineer is responsible for designing, building, and deploying advanced AI and machine learning solutions, collaborating with various teams to ensure operational excellence and scalability.

Lead the development of AI/ML solutions, ensuring compliance with ethical standards, mentoring team members, and integrating AI into broader engineering efforts.

Develop and implement AI/ML strategies, build machine learning models, collaborate with teams, and drive adoption of AI solutions in healthcare.

Drive AI/ML innovations, develop AI solutions, collaborate with teams, ensure compliance, mentor members, and enhance provider experiences in healthcare.

The Staff Machine Learning Engineer will build ML systems to enhance fraud prevention and risk decisions driving platform improvements and mentoring fellow scientists.

Design, implement, and manage complex machine learning algorithms with a focus on computer vision. Experience in MLOps, cloud platforms, and testing AI technologies is essential.

The Staff Machine Learning Engineer will lead Bitcoin risk modeling efforts, drive ML strategy, develop detection models, and mentor teammates.

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.

Develop large-scale Foundation Models for Autonomous Driving & Robotics, collaborating with teams, optimizing model performance, and mentoring junior members.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

As a Senior AI/ML Engineer, lead the design and implementation of AI systems, mentor a team, and drive projects from concept to delivery. Collaborate with cross-functional teams on healthcare-related AI solutions, ensuring quality and innovation in model development.

As a Senior Staff Machine Learning Engineer, you'll build production models, improve machine learning features, and ensure data infrastructure for fraud detection and more. You'll leverage your extensive experience in machine learning and collaborate to drive product intelligence.

The Machine Learning Engineer will design, implement, and manage complex ML algorithms, focusing on computer vision and data analysis while collaborating with team members to transition algorithms to production.

The Machine Learning Engineer will design, implement, and manage complex ML algorithms, focusing on computer vision, testing algorithms, and transitioning them to production. Responsibilities include tracking advancements in ML, conducting experiments, and writing maintainable code.

Lead the design and development of real-time machine learning personalization architecture, focusing on user experience and dynamic content discovery.

Develop and lead the architecture for a unified Global Search system, optimizing for speed and personalization using advanced retrieval logic and integrations, ensuring high-performance search experiences.

As a Senior Staff Machine Learning Engineer, you will design and implement AI infrastructure, collaborate on GPU performance, and mentor colleagues.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

This role involves designing and building advanced ML models to protect against fraud and enhance user experience while mentoring lower-level engineers and influencing technical roadmaps.

The Senior AI/ML Engineer will design and deploy AI/ML models, utilizing GenAI technologies and agentic AI frameworks, while collaborating with stakeholders on large-scale datasets.

Lead the design and deployment of machine learning models for personalized navigation and recommendations, managing projects end-to-end with a focus on user-centric solutions.

Design and deploy ML models for fraud detection, develop data pipelines, partner with teams to ensure effective fraud prevention, and enhance detection accuracy.

The role involves designing, developing, and deploying machine learning models for healthcare applications, collaborating with cross-functional teams, and optimizing model performance.