Top Machine Learning Jobs

The Senior Principal, ML/AI will lead cross-functional teams in developing and implementing ML/AI solutions, driving significant business impact through innovative technical leadership over a defined roadmap.

Lead cross-functional ML/AI initiatives, drive technical roadmaps, mentor teams, and deliver impactful ML/AI solutions for business growth.

The role involves designing and implementing reinforcement learning pipelines for AI systems, integrating organizational data, and collaborating with product teams to enhance AI functionalities.

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.

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.

Build and deploy AI/ML models for various asset categories, design workflows, and quickly prototype solutions using customer data.

Designs and builds core ML systems for AI agents, integrating models and orchestration layers, and ensuring enterprise-ready solutions.

As a Sr. Associate ML Engineer, you'll develop AI solutions for payroll processing, leveraging massive datasets to enhance user experience and efficiency.

The Machine Learning Engineer will lead the development of a semantic intelligence platform, building knowledge graphs and AI software to enhance data accessibility and business insights.

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.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

As a Senior Machine Learning Engineer in the Health team, you'll design and productionize ML systems for personalized health metrics, collaborating with data scientists and engineers to optimize performance and ensure service reliability.

As a Senior Machine Learning Engineer, you will develop machine learning models, manage their lifecycle, build infrastructure, and collaborate with teams to enhance our capabilities in various ML areas.

Lead and develop advanced machine learning models for autonomous driving, collaborating with teams, and driving technical initiatives in a hybrid work environment.

The Machine Learning Platform Engineer maintains and enhances scalable ML systems, collaborates with cross-functional teams, and drives key initiatives in infrastructure and product features.

Lead modeling strategies for AI Bots in League of Legends by developing and implementing ML systems, collaborating with teams, and ensuring player experience enhancement through advanced ML methods.

As a Staff Machine Learning Engineer, you will design and develop VoIP infrastructure and integrate LLMs into voice platforms while enhancing operational practices.

Develop and expand revenue forecasting and dynamic pricing systems, design models to predict demand, optimize pricing strategies and ensure data quality.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

The Principal Machine Learning Engineer will develop ML algorithms and optimize performance on ARM computing platforms, collaborating across hardware, software, and ML algorithms, while focusing on performance, power, and area.

The Staff ML Engineer will design and implement backend components for the ML Inference Platform, ensuring efficient model serving and collaborating with ML teams to enhance AI infrastructure at GM.

Lead research on machine learning validation for robotics and autonomy systems, focusing on simulation, uncertainty modeling, and creating functional prototypes for testing.