Top Senior Machine Learning Jobs

Drive cross-team engineering efforts to improve user experience on Homefeed by implementing large-scale machine learning systems and enhancing data processing efficiency.

The Senior ML Backend Engineer will design and maintain backend services, integrate ML models, and ensure compliance and performance within healthcare workflows, while leading technical initiatives and mentoring team members.

The role involves developing AI-powered solutions for e-commerce, optimizing data pipelines, and deploying ML systems at scale while using technologies like React, TypeScript, and AWS.

Design, build, and deploy machine learning solutions. Collaborate with teams to transform research into practical applications using large datasets.

As a Staff Machine Learning Engineer, you will design and maintain the ML and AI platform, optimize processes, mentor others, and evaluate new technologies.

Lead the design and delivery of ML infrastructure and models, mentor engineers, and drive innovation in AI-powered intelligence at Upwork.

Lead the architecture and development of machine learning systems for personalized care, treatment intelligence, and automation at scale. Collaborate with cross-functional teams and mentor engineers.

Develop and deploy machine learning models for fraud detection and prevention, collaborating with teams and ensuring model performance over time.

The Senior Machine Learning Engineer will develop full-stack tools, collaborate on research, and build production ML systems, optimizing infrastructure for AI startups.

The ML Engineer will design and automate evaluation pipelines, curate datasets, deploy voice models, and ensure model performance while scaling workloads.

The Lead AI/ML Engineer will develop AI systems, optimize ML models, collaborate with teams, and mentor junior members while ensuring quality in software projects.

The Senior Machine Learning Engineer will design and implement ML solutions, collaborate with teams, and contribute to scalable infrastructure enhancements.

This role involves deploying and optimizing machine learning models for autonomous vehicle motion planning, ensuring performance and reliability in production settings.

The Senior Machine Learning Engineer will design, deploy, and manage production ML systems, focusing on optimization and analytics for ad networks, while collaborating across teams.

As an AI/ML Solutions Engineer, you'll design and implement AI/ML models and data pipelines, collaborate on innovation, and ensure compliance with regulations in banking.

Design, build, and deploy ML models, develop APIs, optimize AWS workflows, and implement CI/CD pipelines for scalable ML systems.

The role involves development of EDA workflows, applying ML techniques for circuit design, and optimization of display circuits. Candidates will work with modern AI methods to enhance circuit performance.

The role involves designing and developing machine learning infrastructure and models, consulting on best practices, and building scalable services for AI integration.

As a Senior Machine Learning Engineer, you will design ML infrastructure, build AI features, and collaborate with cross-functional teams while managing large data sets.

As a Staff Learned Behaviors ML Engineer, you will lead the development of reinforcement learning behavior models for autonomous trucks, define data strategies, mentor other engineers, and drive best practices in model development.

As a Senior Associate Machine Learning Engineer, you'll develop and deploy ML models for insurance investment analytics and risk modeling, collaborating with engineers and data scientists to enhance ML systems.

The Staff Machine Learning Engineer will design, develop, and optimize machine learning applications, mentor junior engineers, and conduct research to enhance Quantcast's ML systems.

Design and maintain scalable ML models for logistics. Own end-to-end projects and collaborate with teams to deliver impactful customer features.

The Machine Learning Engineer will design, develop, and maintain production machine learning models and algorithms, ensuring their efficiency and reliability in deployment.

Lead the development and deployment of machine learning solutions that enhance content discovery on Netflix, partnering with engineering and creative teams.