Top Machine Learning Jobs

The Senior Machine Learning Engineer will design tools for agent development, optimize AI systems, and collaborate with teams to implement production-ready solutions.

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

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

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.

Lead data analysis projects using advanced statistical techniques and machine learning models. Develop predictive models, operationalize monitoring pipelines for LLM, and collaborate with teams on data-driven solutions.

As a Software Dev AI/ML Co-op, you will improve development in Cloud Computing and AI/ML, working on data analytics and coding in Python and C++. You'll contribute to model implementations and exploratory data analysis.

The role involves designing and implementing AI and ML solutions for Defense sectors, requiring experience in ML engineering and cloud environments.

As a Machine Learning Subject Matter Expert, analyze ML systems, validate claims, evaluate model performance, and collaborate with teams to report findings.

The Engineering Manager, Machine Learning will lead a team focusing on 3D deep learning and computer vision, manage the ML roadmap, and implement best practices for MLOps pipelines.

The Machine Learning Research Engineer will design and develop robot learning algorithms for manipulation tasks, leveraging large-scale data collection to improve robotic behavior and collaborating with the robotics team.

As an Open-Source Machine Learning Engineer, you'll improve the ML ecosystem using existing libraries and engage with the community, enhancing accessibility to AI tools.

As a Machine Learning Engineer in the Notifications team, you'll design and implement ranking and recommendation systems using LLMs, develop experiments, and collaborate with research teams to improve notification relevance and user experience.

Manage a team of Machine Learning Engineers, architecting systems for content integrity, and ensuring effective model training and deployment.

Lead and mentor a team of machine learning engineers, drive ML projects, and collaborate across departments to enhance product features and model improvements.

Assist in developing AI-powered applications, support workflows, test APIs, optimize data pipelines, and collaborate with teams to build enterprise AI solutions.

Lead end-to-end machine learning solutions for autonomous driving, mentor engineers, design advanced models, and ensure safety and reliability in diverse scenarios.

The Senior AI/ML Engineer will enhance developer productivity by improving Python workflows, leading projects, mentoring engineers, and driving best practices.

Assist in developing and deploying AI and ML features, collaborate with engineering teams, and align AI initiatives with the product vision.

The Senior Machine Learning Engineer will develop foundational models for recommendations, mentor engineers, and collaborate on improving user experiences with machine learning.

The role involves designing ML models, research, improving ML capabilities, mentoring engineers, and managing data at scale utilizing cloud platforms.

As a Lead Research Scientist in Machine Learning, you will develop AI/ML algorithms, lead teams, work on innovative problems, and communicate technical insights.

Develop AI/ML algorithms for signals exploitation, perform modeling and simulations, and engage in project teams for innovative solutions.

The intern will utilize machine learning and statistics to extract patterns from data, implement algorithms, back-test models, and communicate findings effectively.

As Machine Learning Product Director, define ML strategy and manage product development for Attrition Risk Insights, enhancing customer engagement through predictive modeling.

Designs, develops, and deploys machine learning models and scalable data pipelines in production. Performs data discovery, quality analysis, model monitoring, and optimization. Collaborates with data science and business stakeholders to translate requirements, document features, and implement SDLC best practices to drive automated, scalable AI solutions.