Top Machine Learning Jobs

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

Lead cross-functional teams of machine learning engineers and data scientists, driving technical direction and fostering a collaborative environment to develop high-quality ML-driven capabilities.

Design and build LLM based solutions to enhance user playlist experience. Collaborate on product features, prototype and productionize ML systems, and uphold best practices in ML development.

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

Design and deploy scalable machine learning models, analyze datasets, collaborate on ML standards, and communicate solutions to stakeholders.

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.

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.

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.

As a Machine Learning Engineer, you'll develop and ship models for an AI platform, own projects from start to finish, and work closely with customers to enhance product features.

Lead the Applied ML team's experimentation efforts, mentoring scientists and engineers to improve AI-driven methodologies and collaboration across various product areas.

Lead the development and implementation of machine learning solutions, providing strategic direction and fostering an innovative engineering culture. Ensure alignment with business objectives and deliver impactful models.

Lead and mentor a machine learning team, develop and deploy ML solutions, and ensure high-quality execution aligned with business goals.

Lead the development of machine learning systems for fraud detection and risk modeling at scale, collaborating across teams and influencing ML strategy.

The Principal Machine Learning Engineer will lead the technical efforts to enhance search quality through data-driven methods, optimizing AI-driven search systems and collaborating with cross-functional teams.

Develop mathematical models for discounting systems, optimize algorithms, collaborate with cross-functional teams, and drive data-driven decision-making.

Design and maintain ML pipelines and data pipelines, optimize fraud detection models, collaborate with teams, and ensure data quality for high-scale applications.

As a Staff Machine Learning Engineer, you will design and develop ML systems to combat fraud by building data pipelines, integrating data sources, and ensuring high-quality model performance while collaborating with teams.

The Senior Machine Learning Engineer will own the entire ML stack for the Counter Intrusion team, developing innovative solutions, training models, and optimizing algorithms for real-time applications.

Develop and optimize machine learning models, preprocess datasets, collaborate on model deployment, conduct tests, and stay updated on advancements.

The Senior Machine Learning Engineer will build Next-gen AI based search systems, optimize ML architectures, and collaborate on search-related projects within a dynamic team.

Develop ML force fields for materials science, manage data sets, extend ML field accuracy, and collaborate within an interdisciplinary team.

The AI Enterprise Engineer will work with enterprise customers to define model specifications, analyze agent behavior, and benchmark models using Bespoke Labs tools, requiring a strong foundation in AI/ML and production deployment.

Lead the vision, strategy, and execution of the machine learning platform at Flex, focusing on compliance, customer success, and internal operations. Build and mentor a team of ML engineers and data scientists to deliver scalable ML systems.

The intern will help develop feedback-driven AI systems utilizing multimodal data. Responsibilities include building scalable ML pipelines and collaborating with cross-functional teams.

The intern will design and train models using machine learning to investigate molecular functions and enhance molecular design. They will analyze experimental datasets and produce insights connecting model behavior to biological outcomes.