Top Machine Learning Jobs in Leon

As a Senior Applied Machine Learning Engineer, you will develop machine learning solutions, manage project lifecycles, and integrate data into production systems.

The Staff Machine Learning Engineer will design and scale data solutions, build ML pipelines, mentor teams, and improve ML infrastructure for global lending products.

The MLOps Engineer is responsible for GCP setup for machine learning models, ensuring seamless deployment and optimal infrastructure, along with monitoring and compliance.

Build and design machine learning infrastructure for data scientists, optimize resources, deploy models, and monitor MLOps within a satellite data context.

Data Scientists will develop and implement data analysis strategies, communicate findings, and extract meaning from large datasets for government missions.

The Machine Learning Educator will develop and teach ML programs, mentor teachers, and write code to enhance learning at Jane Street.

The role involves applying quantitative analytics to influence business strategies, managing risk, and developing innovative analytics for mortgage performance.

The scientist will lead DEL synthesis and analysis, collaborate with teams to enhance drug discovery through machine learning, and manage cross-functional projects.

The Director of Data Services will lead the data lakehouse strategy, ensuring data quality and governance for product offerings, partnering across teams to enhance data accessibility and ML functionalities.

The Machine Learning Engineer will develop machine learning models, build data pipelines, and collaborate with teams to identify customer needs. Responsibilities include training and validating deep learning models and presenting performance results.

Join a collaborative team to develop AI-driven equity trading signals using machine learning techniques on proprietary datasets.

The Staff Machine Learning Engineer will build and maintain ML/AI infrastructure, provide technical leadership, and collaborate with teams to deliver production-grade ML solutions.

The Human Data Operations Manager will design annotation workflows for ML, establish data benchmarks, and partner with cross-functional teams to enhance evaluation processes.

Lead and manage ads analytics efforts at Netflix, focusing on metric standardization, data tool development, and actionable insights delivery.

Lead the ML privacy vertical, developing algorithms to prevent data leakage, conducting evaluations, and collaborating with engineers to deliver applications.

The Machine Learning Engineer will implement MLOps practices, manage model performance, collaborate with teams, and optimize machine learning pipelines.

Design and implement machine learning models to enhance search relevance and improve the retrieval systems for a better customer experience.

As an intern, you will research and implement algorithms in computer vision and machine learning, developing new features for Sony's digital imaging technology.

Design and develop machine learning models and systems, collaborate with cross-functional teams, and provide mentorship to junior members, focusing on creating impactful recommendation systems.

Design, build, and evaluate ML solutions for Spotify's personalization products, collaborating across teams to enhance user experience and model best practices.

The Director of Machine Learning Science will lead teams in delivering ML solutions, drive innovation in search and personalization, and engage with engineering and product teams.

Assist in developing AI/ML algorithms for drone detection, support ML pipelines, and collaborate on innovative solutions with engineers and data scientists.

The Senior Data Science Workbench Analyst leads automation and cloud optimization projects, enhances data accessibility, mentors junior engineers, and improves security for AI/ML workflows.

As an Applied Scientist (ML), you will develop ML solutions, analyze existing systems, and create impactful ML prototypes and evaluation datasets.

The Senior Data Scientist will analyze pharmacy data, develop predictive models, collaborate with stakeholders, and communicate insights to enhance patient care.