Top Machine Learning Jobs

As a Video Algorithms Intern, develop machine-learning models to enhance video quality and work on encoding formats, focusing on improving mid and low bitrate quality.

Develop innovative machine learning algorithms for protein modeling and design, collaborating with experimental biologists and refining predictions.

Lead training, evaluation, and deployment of ML models for scene understanding and behavior prediction in autonomous vehicles.

The engineer will train, evaluate, and deploy ML models for understanding driving environments, focusing on motion prediction and planning for autonomous vehicles.

You will train, evaluate, and deploy ML models for scene understanding and behavior prediction in autonomous vehicles, while collaborating with engineers.

Responsible for training and deploying ML models for scene understanding, behavior prediction, and planning in autonomous vehicles. Collaborate on designing and analyzing experiments, maintaining evaluation code, and improving model performance.

As a Principal Engineer on the Behaviors team, you will guide the technology direction, lead complex initiatives, and mentor engineers to enhance autonomous vehicle capabilities through ML solutions.

Design and build scalable machine learning systems, mentor ML engineers, and collaborate with internal teams to enhance the ML platform.

The role involves designing and developing machine learning models, integrating AWS services, and collaborating across teams to deliver AI solutions. Responsibilities include maintaining code and optimizing model performance.

Design and build end-to-end software products for autonomous vehicles, leading projects in full-stack development, cloud infrastructure, and machine learning pipelines while mentoring junior engineers.

Design and implement AI systems for defense and intelligence sectors, focusing on machine learning solutions, model deployment, and operationalization.

The Senior Machine Learning Engineer will design and deploy ML models, manage end-to-end ML projects, optimize performance, and build scalable pipelines, focusing on computer vision and NLP applications.

The Senior Machine Learning Engineer will propose and develop innovative solutions using ML and computer vision, working with AI techniques in a defense technology setting.

The Senior ML Engineer for Perception will manage the end-to-end pipeline of ML perception models, focusing on design, optimization, and deployment for real-time applications in vehicles.

The Staff AI/ML Engineer will design and implement scalable ML infrastructure solutions, lead projects, mentor peers, and enhance ML productivity at GM.

The Staff Machine Learning Engineer will lead the development of AI solutions, ensure project delivery, and manage technical teams while interfacing with customers. Responsibilities include designing data pipelines, overseeing machine learning model development, and facilitating customer engagement.

Lead the development of ML solutions to enhance user experience at Babylist. Build recommender systems and personalization features from scratch, collaborating with a cross-functional team.

The Machine Learning Modeler will design and scale intelligent systems for data-driven decision-making, implementing ML pipelines, and collaborating with analytics teams for model production and insights.

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 Lead Machine Learning Engineer, you'll design and implement machine learning applications, collaborate with teams, and ensure model performance at scale.

Lead AI/ML engineering projects, develop predictive models, mentor team members, and collaborate on AI solutions for healthcare challenges.

Design and deploy machine learning solutions across AI use cases, working with cross-functional teams to translate healthcare challenges into scalable systems.

This role involves developing AI/ML applications, collaborating with teams, managing projects, innovating solutions, and mentoring peers while maintaining data quality and technical expertise.

Design and evaluate machine learning models for code understanding using transformers. Develop data pipelines and collaborate with teams for integration.