Top Senior Machine Learning Jobs

Design and implement AI/ML solutions for healthcare, collaborating with teams to translate complex requirements, deploy models, and process large datasets.

As a Senior AI/ML Engineer, you will design and build end-to-end ML systems, manage ML lifecycle workflows, and ensure compliance with AI standards within the healthcare sector.

Lead and mentor ML engineers and data scientists, overseeing ML strategy and development of scalable models for healthcare applications.

As a Senior Machine Learning Engineer, you will enhance diffusion models, conduct research, collaborate on system implementations, and communicate findings effectively.

In this role, you'll develop machine learning models for logistics optimization, retailer underwriting, and growth strategies, collaborating with a skilled team to enhance the marketplace experience.

The role involves applying advanced machine learning techniques to solve perception, prediction, and planning problems in autonomous systems, while also providing leadership and deploying solutions to public roads.

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.

Develop and optimize machine learning models for fraud detection. Collaborate on model deployment and conduct experiments, ensuring data quality and driving innovation in digital trust.

As a Staff Machine Learning Engineer, you'll lead AI product development, leveraging LLMs and embeddings, collaborating on technical strategy and coding performance enhancements.

The Machine Learning Engineer will develop, implement, and maintain machine learning applications, collaborating with teams to solve complex problems and optimize ML infrastructure and performance.

Lead the design and implementation of machine learning applications, collaborate with cross-functional teams, optimize ML systems, and ensure responsible AI practices.

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

Develop and scale machine learning training systems for robotics data, optimize training pipelines, and collaborate with ML researchers to enhance autonomy models.

As Director of AI/ML, lead the ML organization, set technical vision, mentor a high-performing team, and contribute to model development and production deployment.

Engineer III, Machine Learning develops ADAS driving models using reinforcement learning and multimodal data. Collaborates with cross-functional teams for model training and evaluation.

Design, build, and deploy scalable ML systems in healthcare, mentor junior engineers, and collaborate with cross-functional teams to solve clinical challenges.

As a Staff Machine Learning Engineer, you will optimize Quora's ad products by applying machine learning algorithms, taking ownership of systems, and collaborating across teams.

The Senior Manager for Machine Learning will lead the ML team, coordinate initiatives, and enhance product development in a collaborative environment.

The Staff Machine Learning Engineer will develop classification systems for content and creators, building machine learning pipelines, conducting analyses, and collaborating with cross-functional teams for effective solutions.

As a Senior Machine Learning Engineer, you will own ML infrastructure and data systems, scaling them for large volumes of video data and supporting deep learning training and experimentation.

The Staff Machine Learning Engineer will lead the design and implementation of conversion models, establish ML best practices, and collaborate with teams to enhance Pinterest's ad performance.

Design, build, and scale production ML systems (including LLMs) to automate customer support and compliance workflows. Lead technical roadmaps, write high-quality Python code, mentor engineers, ensure secure, scalable architectures, and resolve complex reliability issues.

Design, build, and ship ML-powered product features (search, personalization, recommendations, computer vision). Improve ML platform, pipelines, deployment, monitoring, and data infrastructure. Collaborate cross-functionally to define metrics, iterate models, and deliver scalable, reliable ML systems.

Develop scalable AI/ML software solutions, ensure quality and compliance, optimize performance, and collaborate on real-time systems. Manage data pipelines and models with a firm grasp of best practices.

Develop and maintain a full-stack platform for computational chemists, focusing on drug discovery through machine learning and data infrastructure. Collaborate with interdisciplinary teams to enhance software tools for visualizing molecules and managing workflows.