Top Machine Learning Engineer Jobs

As a Machine Learning Engineer, you will train, test, deploy, and maintain ML models, guiding clients in AI strategy for national security.

Lead the development of GEICO's AI virtual agent platform, overseeing design, implementation, and collaboration with cross-functional teams, while mentoring junior engineers.

The Data Scientist/ML Engineer will design and deploy ML algorithms, assist federal customers in building applications, and contribute to new feature implementation.

The Lead AI/ML Engineer will oversee the design, development, and deployment of AI solutions, manage cross-functional teams, and ensure system reliability and performance in mission-critical environments.

Join the founding team to build Generative Engine Optimization for AI search, transforming algorithms into scalable ML systems and improving brand visibility.

The role involves building, optimizing, and scaling AI agents for finance teams, integrating data sources, and improving AI system performance.

The role involves developing ML systems for customer use cases on the GenAI platform, combining classical and advanced techniques, while collaborating with cross-functional teams.

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

As an ML Infrastructure Engineer, design backend components, enhance platform performance, and drive system improvements while collaborating across teams.

Build and enhance an ML platform supporting the full model lifecycle, scalable training and real-time prediction services, expand NLP capabilities, design data engineering solutions, maintain production reliability, and mentor junior engineers.

Design, build, and ship ML-powered product features (search, personalization, recommendations, computer vision). Improve ML platform, pipelines, deployment, monitoring, and data infrastructure. Collaborate cross-functionally to define metrics, iterate models, and deliver scalable, reliable ML systems.

Lead a team of developers in creating cloud-based solutions using modern technologies, while mentoring peers and collaborating with product managers.

As a Forward Deployed Engineer in ML, you will design and implement machine learning solutions for enterprise clients, ensuring successful deployment and client satisfaction while collaborating with numerous technical teams.

As a Forward Deployed Engineer for ML at Sonar, you will engage with clients to implement and deploy machine learning solutions, ensuring successful integration and production-grade deployments while leading technical discussions and building client relationships.

The role demands a Senior Software Engineer skilled in backend development and ML, focusing on delivering ML solutions that address business challenges across various domains.

The Machine Learning Engineer will enhance AI systems for strategic partners, focusing on model customization and integration in AWS environments while improving performance and collaborating with multiple teams.

The role involves leading the technical design and architecture of AI/ML platforms, managing cross-functional collaborations, and mentoring engineers while ensuring high performance and reliability of the systems.

This role focuses on developing AI/ML algorithms for various applications, requires teamwork with developers and researchers, and involves analyzing datasets and deploying ML models.

The Machine Learning Engineer will propose technical initiatives, lead design discussions, translate challenges into plans, and uphold engineering standards.

Design, build, and deploy production GenAI solutions (including chatbots) for finance use cases. Process structured and unstructured data, implement RAG pipelines, vector DBs, text-to-SQL, integrate with cloud/MLOps, and collaborate with stakeholders and engineering teams.

As a Lead Machine Learning Engineer, you will operationalize ML models, collaborate with teams, solve complex problems, optimize data pipelines, and implement best practices in ML deployment.

As an AI/ML Engineer, you'll implement machine learning techniques, build AI models, and support national security applications, collaborating with various teams.

This role involves training, testing, deploying ML models, and defining ML strategies for military use, requiring strong experience in AI and machine learning techniques.

This role involves building, deploying, and maintaining AI and ML models for national security purposes, collaborating with teams to deliver solutions.

The role involves developing, adapting, and implementing machine learning algorithms for computer vision tasks in power grid analysis. Responsibilities include experimentation, error analysis, and project ownership.