Top Machine Learning Engineer Jobs

Design and deliver machine learning models and cloud-based systems for frontline worker devices, including model training, optimization, and deployment in cloud environments.

As a Machine Learning Engineer - Edge, you will develop and optimize AI/ML models for resource-constrained devices, collaborate with hardware engineers, and ensure model efficiency and reliability.

Develop and optimize advanced machine learning models for product discovery, oversee data processing, and evaluate model performance while collaborating with cross-functional teams.

The Senior Staff Machine Learning Engineer will lead the development of GEICO's AI-driven virtual agent platform, overseeing technical design, cross-functional collaboration, strategic planning, and mentoring within the team throughout project lifecycles.

Design and develop retrieval systems for AI workflows at Zoom, involving machine learning, information retrieval, and multi-tenant architecture. Collaborate with teams to enhance AI capabilities across enterprise data sources.

Develop and optimize processing pipelines and runtime environments for machine learning applications in autonomous trucks, focusing on efficient resource utilization and SDK feature development.

As a Machine Learning Engineer, you will design, build, and maintain ML systems, fine-tune LLMs, and translate ML research into scalable solutions.

The Machine Learning Engineer will design and develop deep learning architectures, optimize models, analyze datasets, and collaborate to enhance manufacturing processes across Howmet Aerospace.

The ML Engineer will build and deploy machine learning models to optimize operations in manufacturing, including demand intelligence and production monitoring.

Lead the design and development of machine learning solutions, overseeing the entire software development lifecycle and mentoring engineers. Drive innovation in Generative AI and high-performance systems.

The AI/ML Engineer will develop scalable machine learning systems for cyber analysis, enhance existing applications, and participate in agile team activities.

As Lead ML Engineer, you will architect and build a conversational AI interface, optimize models for deployment, and collaborate with a multidisciplinary team.

The Senior Vision AI Engineer will develop and deploy computer vision and machine learning models, create optimized vision pipelines, and mentor junior engineers, focusing on industrial applications.

The Senior AI/ML Engineer at Cooley will design, build, and maintain enterprise-scale AI/ML solutions across cloud platforms, optimize performance, and collaborate on AI implementations.

The Staff Machine Learning Engineer will lead ML systems development for personalization and ranking, design architectures, and mentor team members, ensuring reliable operations at scale.

As a Senior Software Engineer, you'll enhance servicing decisions with ML models, improve experimentation, and scale decisioning systems for personalized borrower experiences.

Summer PhD internship building and deploying production ML models for search, recommendations, and matching. Collaborate with engineers and data scientists on experimentation, model evaluation, monitoring, and documentation to improve product discovery and user experience.

The Lead Machine Learning Engineer will design and build ML models, collaborate with teams, ensure model performance, and utilize cloud technologies for optimized deployment.

This role involves developing and optimizing machine learning models for autonomy, managing datasets, enhancing training pipelines, and collaborating across teams to integrate ML solutions in autonomous vehicles and delivery robots.

The Staff ML Engineer will define and build ML capabilities, focusing on production systems, strategy, and infrastructure in a cybersecurity context.

As an AI/ML Engineer, you'll design, build, and ship large scale NLP and LLM systems for classification, ranking, and content generation while collaborating with cross-functional teams.

The Machine Learning Engineer will develop ML infrastructure, optimize models for anomaly detection, and manage technical projects to enhance space cybersecurity.

The Machine Learning Engineer will train, fine-tune, and deploy ML models for parsing unstructured data, and build data pipelines for product integration.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

The AI/ML Engineer will identify and scale generative AI technologies, lead pilot projects, collaborate on implementations, and refine AI outputs.