Top Machine Learning Engineer Jobs

The Lead AI/ML Engineer evaluates emerging technologies, leads teams in adopting solutions, and provides technical leadership while mentoring junior specialists.

The Machine Learning Engineer will develop machine learning models, build data pipelines, and collaborate with teams to identify customer needs. Responsibilities include training and validating deep learning models and presenting performance results.

The Staff Machine Learning Engineer will lead ML strategy, architect AI infrastructure, mentor engineers, and develop impactful AI systems.

This role involves designing, training, and evaluating ML models, collaborating on AI initiatives, and optimizing model performance for practical applications.

The Machine Learning Engineer will build a robot-learning stack, design training infrastructure, deploy ML policies, and collaborate with engineers in heavy manufacturing.

The role involves architecting AI systems, developing algorithms for optimization and building hybrid search systems. You will lead MLOps processes and collaborate across functions to deliver AI-first products.

The Principal ML Engineer will design and scale ML infrastructure for scientific discovery, collaborating with AI scientists to enhance model training and deployment processes.

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

Design and scale infrastructure for machine learning models, build pipelines, and optimize for performance in a collaborative remote environment.

Lead and architect the technical strategy and roadmap for Content Quality at Pinterest, focusing on building signals for content quality and collaboration with ML engineers on deployment.

Develop and optimize ML models for ad-serving and search solutions, manage AI/ML projects, and implement best practices in MLOps.

The Lead Machine Learning Engineer will manage AI/ML project lifecycles, collaborate with teams on model optimizations, implement best practices in MLOps, and mentor juniors while ensuring model reliability.

The Senior Machine Learning Engineer will design and implement ML systems, oversee data pipelines and model management, and guide technical strategy while collaborating across teams to deliver production-ready models.

As an Applied Machine Learning Engineer, develop, deploy, and optimize machine learning models while collaborating with cross-functional teams to enhance customer solutions.

As a Senior/Principal Machine Learning Engineer, you'll design and build core ML systems for Workday's AI agents, collaborating with cross-functional teams on models and deployment for real-world applications.

The Associate Machine Learning Engineer will develop and enhance machine learning models and features to optimize user experience, collaborating with senior engineers and data scientists.

As a Principal Machine Learning Engineer, you will develop distributed inference infrastructure, integrate with vLLM, and optimize inference workloads, mentoring fellow engineers along the way.

As a Staff Software Engineer, you'll lead machine learning infrastructure projects, focusing on model deployment, monitoring, and lifecycle management while ensuring team collaboration and cross-team goals.

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.

Design and deploy machine learning models for personalized recommendations and search on Zillow's platforms. Collaborate with cross-functional teams to enhance user experience.

The Senior AI ML Engineer will design and implement AI workflows, automation solutions, and integration patterns, ensuring productivity and accuracy across the organization while mentoring engineers and enforcing responsible AI practices.

The candidate will design and implement machine learning solutions, collaborate with data teams, optimize models, and ensure production readiness of ML systems.

As a Machine Learning Engineer, you will build and optimize models and systems for protein design, enhancing ML pipelines and infrastructure to support scientists.

Develop and optimize medical large language models, collaborate with interdisciplinary teams, and maintain state-of-the-art machine learning techniques to enhance medical education and clinical decision support.

As a founding Machine Learning Engineer, you will improve core models, optimize LLM inference, develop data pipelines, and ship features directly to users.