Top Machine Learning Jobs

Train personalized ML models, create synthetic data pipelines, evaluate model quality, and develop safeguards for AI privacy and misuse.

As a Machine Learning Engineer, you will design and deploy advanced models for clinical reasoning, manage ML systems, and collaborate with teams to enhance healthcare delivery.

Design, train, and deploy machine learning models for detecting malicious content, working with large datasets and collaborating with teams to enhance system scalability.

As an AI/ML Engineer Intern, you will apply AI to enhance restaurant discovery experiences by analyzing data, building models, and collaborating with teams.

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

The Machine Learning Engineer role at Patreon involves developing machine learning models, analyzing data, collaborating across teams, and deploying solutions to enhance creator support.

Develop and deploy machine learning models for national security challenges. Responsibilities include algorithm development, model training, deployment, and collaboration with teams for effective ML solutions.

Develop and productionize ML models for assessing autonomous vehicle behavior, build ML infrastructure, and collaborate across teams for deployment.

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.

As a Senior Applied AI Engineer, you will develop and deploy machine learning models, improve system performance, and drive AI initiatives at Databricks.

As a Quantitative Research Intern, you will research and develop autonomous trading strategies using AI and machine learning on large datasets, collaborating with experts in the field.

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.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

Develop and scale machine learning systems for physiological signal processing. Design and train models, ensure compliance, and mentor team members while collaborating with cross-functional teams.

Conduct research and develop machine learning models for finance, focusing on deep learning and large language models, optimizing them for performance, and collaborating with teams to integrate ML solutions.

Conduct ML and deep learning research to build, test, and deploy predictive models for trading. Collaborate with traders, researchers, and engineers to engineer features, preprocess data, prototype algorithms, and improve production research tooling to enhance trading performance.

Lead development and deployment of ML models for trading, drive research and prototyping, oversee data and feature engineering, mentor researchers, and build scalable ML research infrastructure.

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 Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

The Senior Machine Learning Engineer will architect the ML infrastructure, productionize models, maintain data platforms, and ensure system health, collaborating closely with data scientists and data engineers.

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.

As an Applied Scientist II, you will work with cross-functional teams on projects that optimize software systems and improve ML components, while analyzing inefficiencies and proposing solutions.

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.