Top Machine Learning Jobs

The role involves R&D and software development in machine learning, focusing on algorithm development, data processing, and prototype development for various applications.

As an AI/ML Engineer, develop and optimize analytics frameworks to enhance autonomous vehicle development, focusing on automation tools and collaboration with engineering teams.

Develop and implement large-scale machine learning models to enhance user ad predictions and better understand user interests through data mining and collaboration with product teams.

The Sr. Machine Learning Engineer/Data Scientist will develop machine learning models, drive data-driven decisions, mentor others, and lead strategic projects in eCommerce.

Lead the Embeddings Platform Team, architecting and maintaining foundational ML embeddings, driving projects, and building a high-performing team to support machine learning initiatives across Reddit.

The Senior Sentinel Developer will create and implement machine learning algorithms to support intelligence missions, integrating data and optimizing technological solutions.

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.

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.

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

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

The Principal AI/Machine Learning Engineer will lead the adoption of AI/ML in manufacturing by defining use cases, driving implementation, and ensuring organizational readiness.

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

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

As a Machine Learning Intern, you'll develop models to translate brain wave data into useful forms, collaborating across ML and software efforts.

Lead Machine Learning Engineer responsible for building and deploying models to translate brain data. Manage team and work across ML stack.

The role involves using mathematical and computational methods for data modeling, analysis, and algorithm development, requiring expertise in machine learning and advanced statistics.

The role involves developing advanced ML models for scene understanding and managing the end-to-end ML pipeline from data gathering to deployment.

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.

As an Applied AI ML Lead, you will design and implement machine learning models, manage data processing pipelines, and collaborate with teams to meet business needs.

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.

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.

This role involves developing AI/ML applications, collaborating with teams, managing projects, innovating solutions, and mentoring peers while maintaining data quality and technical expertise.