Top Hybrid Machine Learning Engineer Jobs

The Senior Applied AI/ML Scientist will lead the design and deployment of AI solutions, collaborate on impactful features, and enhance product capabilities by leveraging advanced AI and ML techniques.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

As a Principal Machine Learning Engineer at Zscaler, you will lead AI/ML projects, optimize systems, and collaborate on cybersecurity solutions while mentoring engineers.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

Lead the design and development of Datadog's experimentation engine, translating complex statistical methods into production systems while collaborating with cross-functional teams and educating stakeholders on best practices.

Develop and deploy state-of-the-art reinforcement learning algorithms for dynamic locomotion and manipulation on humanoid robots. Drive simulation-to-hardware transfer, build and optimize distributed training pipelines, mentor junior engineers, collaborate with hardware teams to debug system-level issues, and convert human demonstration data into robust reference trajectories.

As an Applied Machine Learning Engineer, you will develop AI and ML models to improve healthcare outcomes. Collaborate with teams to implement and optimize machine learning techniques and algorithms.

Manage financial markets risk portfolio by applying statistical and machine learning models to optimize forecasting and decision-making. Collaborate with cross-functional teams to provide actionable insights.

Develop scalable AI/ML software solutions, ensure quality and compliance, optimize performance, and collaborate on real-time systems. Manage data pipelines and models with a firm grasp of best practices.

Develop ML force fields for materials science, manage data sets, extend ML field accuracy, and collaborate within an interdisciplinary team.