Top Machine Learning Jobs

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

Seeking an experienced Machine Learning Engineer to design and deploy scalable machine learning and NLP solutions, mentor junior engineers, and collaborate on data-driven projects with cross-functional teams.

Lead the development of pricing algorithms for vehicle valuation at CarMax, managing a team of data scientists to implement strategies and maintain optimal pricing models.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

As a Senior Applied AI/ML Associate, you'll design AI solutions, analyze data, and enhance client interactions through ML techniques, while collaborating with teams to implement models.

The role involves designing and deploying machine learning models, optimizing large language models, and collaborating with cross-functional teams to enhance data management for alternative investments.

Conduct research and develop machine learning models for financial contexts, focusing on LLMs and deep learning applications. Collaborate to integrate solutions into trading strategies.

As a Staff Applied Machine Learning Engineer, you'll design and implement LLM applications, integrating ML features to enhance user experiences and scalable services.

Lead the development of ranking and relevance models, design ML systems for patient-provider matching, and mentor junior team members.

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.

Join Braze as a Senior Software Engineer to enhance our ML platform, focusing on scalable AI solutions and robust coding practices. Collaborate across teams to leverage data infrastructure and implement ML models in production.

As a Senior Software Engineer specializing in Machine Learning, you will design and scale Braze's AI platform, focusing on data architecture and production-level ML implementations.

Lead a team focused on machine learning solutions, overseeing project execution, designing AI/ML infrastructure, and mentoring engineers towards excellence in scalable ML implementations.

Develops and implements machine learning methodologies, manages cloud applications, and develops backend components to improve system performance. Responsible for documentation and testing phases.

The AI Intern will experiment with machine learning technologies, evaluate model performance, explore AI patterns, and document findings in progress reports.

Lead the development of AI and machine learning pipelines for Revenue Cycle Management, collaborating across departments to optimize processes and enhance financial performance.

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

Develop and deploy machine learning applications, collaborating with teams to solve business challenges. Create ML solutions, analyze data, and communicate results.

The Senior Machine Learning Engineer will own the entire ML stack for the Counter Intrusion team, developing innovative solutions, training models, and optimizing algorithms for real-time applications.

Design, build, and deliver machine learning models and components. Ensure performance and monitor models in production as part of an Agile team.

The role involves designing, developing, and supporting AI and ML products, collaborating with teams to transform risk management and deliver value to customers through technology.

The Senior Machine Learning Engineer will design and optimize ML models, manage end-to-end ML projects, and enhance SailPoint's AI capabilities while collaborating with various teams to integrate AI features into products.

The AI Enterprise Engineer will work with enterprise customers to define model specifications, analyze agent behavior, and benchmark models using Bespoke Labs tools, requiring a strong foundation in AI/ML and production deployment.

The Machine Learning Engineer will scale core infrastructure, manage data pipelines and model evaluation, and improve benchmarking systems. Collaborate with teams to enhance AI evaluation methodologies.

Manage and lead a team in developing machine learning algorithms for driving models. Oversee strategy, technical guidance, performance monitoring, and resource allocation for Offline ML models.