Top Machine Learning Engineer Jobs

The role involves shaping the CV strategy, building ML solutions in production, and integrating them with software systems, focusing on computer vision applications.

Design, build, and productionize ML models; maintain data pipelines; collaborate with teams to deliver AI features and enhance product experiences.

Lead the development of a robotics data platform, focusing on data enablement, API architecture, and mentoring engineers in complex system designs.

The ML Engineer will develop and deploy machine learning models, collaborate with teams, analyze datasets, and improve model performance.

The R&D Engineer will design and implement performance workloads on Cerebras' wafer-scale hardware, collaborating across teams to advance AI and scientific computing. Responsibilities include optimizing performance models, contributing to the technology roadmap, and publishing research findings.

Develop and deploy machine learning models for decision-making in autonomous trucks, focusing on learned behavior systems and model performance improvements.

The Senior Machine Learning Engineer will design, develop, and deploy machine learning solutions for Vitol, working across trading and operations with various stakeholders.

Design and build a production-grade agentic workflow platform, integrating large language models and implementing orchestration, reliability, and extensibility for real-world business use.

Oligo seeks a Software Engineer with expertise in ML/AI to develop algorithms for generative design and optimization in spacecraft systems, collaborating with engineers to apply cutting-edge AI to hardware.

As a Senior Machine Learning Engineer, you'll design data pipelines, develop prediction systems, and optimize model deployment processes while collaborating with cross-functional teams.

The Senior Machine Learning Engineer at GEICO will design, develop, and deploy AI solutions, mentor junior staff, and collaborate with cross-functional teams to drive business value and innovation in generative AI workflows.

Develop and deploy production-grade AI/ML models, design end-to-end pipelines, and ensure compliance while collaborating with stakeholders in a federal environment.

Support customer network operations with systems engineering and project management by analyzing AI/ML proposals, coordinating activities, and improving processes.

Design, develop, and implement ML pipelines and collaborate with teams to integrate models, optimize techniques, mentor engineers, and communicate effectively.

The ML Research Engineer will implement and deploy deep-learning models for perception AI, manage data pipelines, and design user interfaces.

The role involves designing ML pipelines for computer vision, optimizing models for edge deployment, and developing data management systems for sensor datasets.

The Senior Software Engineer will develop and optimize algorithms and ML models for mobile, embedded, and cloud environments. Responsibilities include collaborating with cross-functional teams, deploying algorithms, analyzing performance, and ensuring code quality.

Develop algorithms in machine learning and statistics to address complex challenges. Design data pipelines and deploy solutions using cloud infrastructure.

The Software Engineer will build components for Red Hat's AI platform using Python, implement features and collaborate with senior engineers, while participating in agile ceremonies.

Responsible for designing and implementing scalable ML software solutions for Search & Discovery, processing massive datasets, and optimizing ML pipelines for real-time applications.

The Senior Machine Learning Engineer will lead applied research projects, design and implement ML models, maintain data pipelines, and mentor junior members for defense-focused missions.

Responsible for designing, building, deploying, and maintaining production-grade AI and ML solutions in a cloud-native environment, while collaborating with engineering and data teams.

The role involves designing and developing machine learning infrastructure for annotation, evaluation, and training models, focusing on scalable systems and efficient data workflows.

The Data Engineer will modernize Business Intelligence capabilities, design data pipelines, deploy ML solutions, and collaborate across teams to improve data processes.

The Senior Machine Learning Engineer will design, train, and evaluate ML models to solve complex problems, mentor others, and optimize production systems.