Top Hybrid Machine Learning Engineer Jobs

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.

The Machine Learning Engineer Senior will design and develop ML algorithms to enhance analytics and decision-making, optimizing model performance, and ensuring reliability and data quality.

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.

Conduct ML and deep learning research to build, test, and deploy predictive models for trading. Collaborate with traders, researchers, and engineers to engineer features, preprocess data, prototype algorithms, and improve production research tooling to enhance trading performance.

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.

As a Senior Machine Learning Engineer, you will develop machine learning models, automate data pipelines, and collaborate with teams to meet customer needs.

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.