Top Machine Learning Jobs

The Machine Learning Modeler will design and scale intelligent systems, build forecasting models, and collaborate with analytics teams to make data-driven decisions at Block.

Develop and deploy ML models to combat financial crimes. Collaborate with cross-functional teams, maintain documentation, and lead ML best practices.

Lead the development of advanced machine learning models and AI solutions for customer support, focusing on chatbot and voice automation technologies.

The Senior Machine Learning Engineer will develop scalable ML systems, collaborate across teams to improve solutions, and manage critical ML infrastructure projects.

The role involves advanced data analysis, designing data solutions, developing machine learning models, collaborating across teams, and providing strategic insights to improve business decisions.

As a Principal AI/ML Software Engineer, you'll lead ML technology strategy, develop innovative solutions, and influence technical decisions across the organization while guiding high-performing teams.

The Principal AI/ML Software Engineer will drive ML technology strategy, lead cross-functional initiatives, and develop innovative ML solutions while guiding teams in technical vision and architecture.

The Principal AI/ML Software Engineer drives ML technology strategy and innovation, develops solutions for complex problems, and leads cross-functional initiatives while shaping the technical vision and architectural frameworks for AI/ML.

The Staff Machine Learning Systems Researcher will model performance of Lightmatter systems, collaborate on designs, publish research, and stay updated on ML advancements.

The Machine Learning Engineer will develop and deploy AI/ML solutions, collaborate with data scientists and engineers, and enhance the platform experience.

The Senior AI Scientist will lead ML/AI innovation for multimodal video models, develop production-grade ML models, and engage in research and representation at conferences.

The role involves designing and maintaining machine learning models, analyzing data, and optimizing algorithms to solve business problems.

Design and implement machine learning models to solve business problems, analyze data for insights, and optimize model performance.

As a Machine Learning Engineer, you'll analyze data to optimize products for the ad platform, enhance ad relevance, and design performance models.

Develop applications for machine learning and generative AI technologies, automate data analysis, and collaborate on prototyping solutions for semiconductor testing.

The role involves building and improving systems for training AI models, focusing on algorithms and infrastructure for reinforcement learning. Responsibilities include enhancing performance, reliability, and usability of systems to support research.

Develop machine learning models to differentiate normal and attack behaviors, collaborate with security researchers, and analyze algorithm performance.

Interns will design and implement ML models, develop RAG pipelines, integrate AI solutions with Azure, and research solutions.

As a Staff Machine Learning Engineer at Angi, you'll lead model development, deploy MLOps solutions, collaborate across teams, foster innovation, and mentor juniors to enhance machine learning capabilities.

Conduct applied research in robotics and develop ML pipelines for training models on data collected by Scale, collaborating with customers and cross-functional teams.

Support Acute Care Informatics by developing ML/AI solutions; collaborate with clinicians to enhance clinical data analytics through algorithms and cloud technologies.

The Senior Engineer in Machine Learning will develop algorithms using machine learning techniques on biomedical datasets, prototype solutions, and collaborate with teams to ensure data quality and performance measures.

Lead and implement machine learning solutions for clinical trials, collaborate on predictive modeling, and oversee data governance, optimizing patient outcomes.

Oversee strategic development and execution of analytics and machine learning initiatives. Mentor teams, manage projects, enforce data governance, and collaborate cross-functionally.

Drive and implement machine learning applications, optimize practices, formulate hypotheses, and communicate requirements to enhance advertising strategies and systems.