Top Senior Machine Learning Jobs

The Lead Machine Learning Engineer designs and implements ML applications, builds data pipelines, collaborates with teams, and ensures performance and governance of ML systems.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

The Senior Machine Learning Engineer will design and implement ML systems, collaborate with data scientists, and enhance analytics capabilities to improve game design and player engagement.

Design, implement, and deploy machine learning models and systems for recommendations and related problems. Collaborate with engineers, data scientists, and product partners to analyze data, build proofs-of-concept, develop ML/optimization models, write production-quality code, and evaluate models against business goals.

Design and deploy machine learning models for content relevance on Patreon. Collaborate with cross-functional teams, analyze data, and iterate on models for performance improvement.

The Research Engineer will develop and deploy machine learning applications focused on severe weather, collaborating on system processes, and maintaining production environments.

As a Senior Machine Learning Engineer, you will design and implement systems for ML and NLP, optimizing models and tools for Clover's healthcare solutions.

As a Machine Learning Engineer, you'll own the design, development, and operation of production-grade ML systems in clinical workflows, ensuring model accuracy, reliability, and integration into patient-facing applications.

The Senior Machine Learning Researcher will design experiments, research new algorithms, and collaborate on deploying models for computer vision and robotics applications.

The Staff Applied Scientist will develop machine learning models for forecasting, collaborating with cross-functional teams to improve advertising campaigns, and drive model development using data.

As an Applied Scientist, you will develop ML and deep learning models for forecasting in advertising campaigns, collaborate with engineers and product teams, and continually improve model performance based on data-driven insights.

As a Staff Applied ML Scientist, you will develop and maintain fraud detection models, conduct research on fraud types, and collaborate across teams to drive product development and real-time decision-making.

As a Senior Applied ML Scientist, you'll develop fraud detection models, research new fraud types, and write production code while collaborating across teams to enhance SentiLink's identity verification solutions.

Lead the development of AI/ML systems in robotics and manufacturing, designing ML architectures, and collaborating with cross-functional teams.

The Lead Machine Learning Engineer will design, build, and deploy machine learning models and data pipelines, ensuring high performance and governance of ML applications while collaborating in an Agile environment.

Drive technical strategy for the Personalization Platform, develop recommendation systems, maintain ML workflows, and innovate AI solutions for customer engagement.

Lead the engineering organization for the Personalization Platform at Capital One, focusing on real-time AI-driven personalization, managing ML infrastructure, and building high-performing teams.

The Senior Full Stack AI Developer will build and maintain solutions using machine intelligence, develop automation code, and advise on simple and secure solutions while managing microservices.

This role involves leading the development of AI systems to replace lab toxicity experiments, focusing on end-to-end ML architecture, research on chemistry-biology correlations, and building innovative models. Candidates should have strong ML skills, engineering abilities in Pytorch and Python, and a passion for both science and technology.

Design and optimize machine learning algorithms for sectors like energy and healthcare. Conduct simulations, validate performance, and collaborate with teams.

The Senior ML Software Engineer will create and improve capabilities for mapping data using machine learning, collaborating with engineers and data scientists, developing models, and writing production code.

Design and evaluate machine learning algorithms focused on autonomy and perception, prototype solutions, conduct experiments, and transition prototypes into production.

The Senior Analyst will develop AI and ML algorithms, optimize data systems, and present research findings. Requires extensive experience in model development, system architecture, and MLOps.

Lead the design, development, and implementation of machine learning applications; collaborate with Agile teams to optimize performance and scalability.

Lead design, build, and deployment of scalable ML/AI models (including image/vision) to production. Collaborate with engineering and business teams, monitor model quality and bias, and apply data-driven solutions to predict and aggregate risk.