Top Machine Learning Jobs

The Lead Machine Learning Engineer will lead data and ML system development, manage technical challenges, and streamline data science initiatives within the AI Platform team at Visa.

Develop and apply machine learning models for antibody properties prediction, contribute to optimization workflows, and collaborate with experimental teams in drug discovery.

As a Machine Learning Engineer at Quantcast, you'll design, code, and maintain ML applications, conduct experiments, and optimize systems for scalability while collaborating with engineering teams.

Design and implement optimizations for llama.cpp, focus on performance analysis, collaborate with open-source community, and enhance machine learning deployments.

Develop and deploy Machine Learning models as part of a data team. Collaborate with engineers, analysts, and scientists. Innovate across ML fields.

The Research Engineer will develop and deploy machine learning models and systems, collaborate with teams, and mentor junior members while staying updated on research trends.

Assist in developing and deploying machine learning models and AI solutions by collecting data, optimizing model performance, and collaborating with teams.

Lead the development of machine learning technologies within Ads Ranking, enhance user experience, and improve engineering systems in a collaborative environment.

The Senior Machine Learning Engineer develops machine learning models, collaborates on data-driven solutions, analyzes datasets, and ensures AI model efficiency.

The role involves developing advanced machine learning solutions, collaborating with experts, and managing ML model architecture and deployment.

The Machine Learning Developer will work on data pipelines, monitor model performance, contribute to CI/CD processes, and research new AI/ML technologies.

The Staff Software Engineer will architect and implement backend systems for LLM applications in healthcare, focusing on APIs, data pipelines, and compliance.

The Machine Learning Engineer will develop and test GenAI architectures, fine-tune LLMs, apply ML algorithms, and contribute to architectural design in a collaborative environment.

The Senior Machine Learning Engineer will lead projects in data engineering and data science, creating scalable data pipelines and predictive models, while collaborating with product and engineering teams to drive impactful outcomes.

The role focuses on machine learning, especially in video and image embedding, and improving user features using ML recommendations. Requires expertise in GCP and video production metrics.

Seeking a Senior Staff Machine Learning Engineer to lead AI/ML system development, optimize architecture, and mentor teams while managing complex ML challenges.

The Machine Learning / Data Engineer will develop data pipelines, contribute to ML model development, collaborate with teams, and maintain high code quality.

As a Staff ML Software Engineer, you will lead the development and deployment of machine learning applications, leveraging your expertise to drive software architecture decisions, maintain cloud infrastructure, and collaborate within a small, agile team focused on geospatial challenges related to climate change.

This role involves designing and implementing machine learning solutions, managing software production, and collaborating with cross-functional teams, with a focus on product ownership and decision-making.

As a Machine Learning Engineer, you'll develop distributed training systems, optimize large-scale model performance, and create efficient data processing pipelines.

Develop advanced biological models for biomolecule design, work with ML frameworks, and enhance model performance through experiments.

The Principal ML Data Engineer will analyze data to develop KPI-driven solutions, build predictive models, and collaborate with engineering and product teams.

Develop and scale learning architectures for behavior cloning and reinforcement learning, build data pipelines, and deploy models in real environments.

Develop and optimize ML models for robotics, collaborate with vendors for data labeling, and evaluate model performance in the field.

The ML Engineer will develop distributed training systems, optimize model performance, and manage data pipelines for efficient large-scale training.