Top Machine Learning Jobs

This role involves developing ML models for Hinge, collaborating with teams, deploying models, and optimizing systems for performance and cost.

The Senior Staff Machine Learning Engineer will develop AI-powered solutions, mentor engineers, and collaborate with cross-functional teams to enhance Airbnb's customer experience through advanced machine learning technologies.

Lead and mentor a team of machine learning engineers, drive ML projects, and collaborate across departments to enhance product features and model improvements.

As a Machine Learning Engineer in the Notifications team, you'll design and implement ranking and recommendation systems using LLMs, develop experiments, and collaborate with research teams to improve notification relevance and user experience.

Manage a team of Machine Learning Engineers, architecting systems for content integrity, and ensuring effective model training and deployment.

The role involves designing and implementing reinforcement learning pipelines for AI systems, integrating organizational data, and collaborating with product teams to enhance AI functionalities.

The Senior Principal, ML/AI will lead cross-functional teams in developing and implementing ML/AI solutions, driving significant business impact through innovative technical leadership over a defined roadmap.

Lead cross-functional ML/AI initiatives, drive technical roadmaps, mentor teams, and deliver impactful ML/AI solutions for business growth.

Develop and integrate real-time AI/ML solutions for autonomous vehicles. Collaborate with teams for deployments in defense scenarios and optimize machine learning models.

Senior Software Engineer role focused on building AI capabilities for an engineering AGI product. Collaborate with a team to integrate cutting-edge machine learning into real-world engineering systems and shape product design.

Assist in developing and deploying AI and ML features, collaborate with engineering teams, and align AI initiatives with the product vision.

The Senior Machine Learning Engineer will develop foundational models for recommendations, mentor engineers, and collaborate on improving user experiences with machine learning.

The role involves designing ML models, research, improving ML capabilities, mentoring engineers, and managing data at scale utilizing cloud platforms.

The intern will develop, deploy, and operate machine learning models, driving research projects to solve real-world problems and collaborate with senior engineers on identifying use cases for ML on blockchain.

The Senior ML/AI Software Engineer will build analysis algorithms and maintain evaluation dashboards for GM's autonomy stack performance, leveraging large datasets and statistical methods.

The Senior Machine Learning Engineer leads technology projects, mentors engineers, and collaborates on cloud-based solutions, primarily using languages such as Python and Java.

Lead the development of production-grade ML systems, aligning technical roadmaps with company priorities, mentoring ML engineers, and ensuring ethical use of ML/AI.

Design and build AI-powered consumer products, partner with cross-functional teams, and lead the development of machine learning systems.

The role involves analyzing healthcare data, building advanced AI/ML models, collaborating with business teams, and deploying production-level models.

The role involves designing and scaling ML systems for prediction and recommendation, mentoring junior engineers, and leading projects.

The intern will conduct research on machine learning and driving behaviors, work with driving datasets, collaborate on deploying results, and publish findings.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

Design and deploy production-grade ML systems, integrate models into software pipelines, and develop features leveraging ML for optimization and prediction problems.

Lead the design and deployment of machine learning models for personalized navigation, collaborate across teams, and drive technical excellence in ML practices.