Top Senior Machine Learning Jobs

The role involves developing an AI agent platform, building ML models, and enhancing user experiences with advanced algorithms. Collaboration and fast-paced execution are key.

As a Senior Principal Machine Learning Engineer, you'll lead technical projects, mentor teams, and implement ML systems, focusing on AI in AEC solutions.

Lead the Applied Machine Learning team at ExtraHop to develop systems for behavioral detection in network security. Manage model design, evaluation, and operationalization while maintaining experimental rigor and collaborating with product teams.

Lead the development of pricing algorithms for vehicle valuation at CarMax, managing a team of data scientists to implement strategies and maintain optimal pricing models.

The role involves developing machine learning models for cash forecasting, collaborating with stakeholders, and owning the ML lifecycle from development to deployment.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Staff Machine Learning Engineer will design backend software components, ensuring platform performance and reliability, while integrating GPU hardware and leading large initiatives within GM's AI ecosystem.

The Machine Learning Engineer will design, build, and deploy ML applications at scale, collaborating with cross-functional teams and applying best practices in ML engineering and cloud technologies.

Lead a team of Machine Learning Engineers in designing, building, and implementing ML applications, focusing on data-intensive solutions and infrastructure decisions, while promoting best practices in AI.

Lead and build a Machine Learning team, driving strategy and execution across product areas like Document Generation and Voice Agents while collaborating with Product and Engineering.

Develop and operationalize machine learning models for lab automation, leveraging multimodal data and ensuring reliable predictive capabilities in drug discovery processes.

Design, build, and deploy AI features for claim synthesis; implement machine learning solutions and improve model performance through collaboration and evaluation.

Lead machine learning initiatives, oversee product development, improve execution pace, enhance team reliability, and foster team growth at Hightouch.

As a Machine Learning Engineer in Fraud Risk, you'll build and maintain ML systems for fraud detection and anomaly analysis, ensuring robust performance and real-time decision making.

Lead the design and implementation of advanced ML models for autonomous driving, collaborating with teams, mentoring engineers, and driving technical initiatives.

As a Principal Machine Learning Engineer, you will develop multimodal AI experiences, design agent interactions, and lead cross-team initiatives while ensuring AI safety and reliability.

Manage and grow the ML team, define goals and metrics, drive ML initiatives, build evaluation processes, and collaborate cross-functionally to enhance product delivery.

You will lead and manage a team of engineers developing machine learning solutions for perception product challenges in autonomous driving.

Design and develop geometry processing algorithms and simulation models, manage datasets, and enhance machine learning workflows for engineering applications.

Responsible for bioinformatics ML/AI application development in clinical settings, designing and deploying ML/AI solutions, and collaborating with multidisciplinary teams.

The Lead Machine Learning Engineer will manage AI/ML project lifecycles, collaborate with teams on model optimizations, implement best practices in MLOps, and mentor juniors while ensuring model reliability.

The Senior Machine Learning Engineer will lead technical strategy, build and maintain ML systems, and enhance engineering practices while ensuring data security and compliance.

As a Staff ML Research Engineer, you will develop and optimize ML algorithms for drug discovery, transitioning high-impact prototypes into robust products and managing software development across the lifecycle.

Lead the design and implementation of machine learning applications, collaborate with cross-functional teams, and build data pipelines. Ensure high performance and governance of ML systems while using best practices in Agile methodologies.

Lead the development and deployment of AI and machine learning models, mentor junior data scientists, and collaborate with cross-functional teams to align solutions with business goals.