Top Senior Machine Learning Jobs

The Machine Learning Engineer will develop and maintain ML deployment pipelines, operationalize AI models, and ensure system reliability and scalability.

The Senior Machine Learning Engineer will automate healthcare compliance workflows using AI to process unstructured data, build multimodal AI pipelines, and develop extraction systems, ensuring high reliability and operational efficiency.

The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.

Design and implement machine learning models, optimize algorithms, deploy solutions, and collaborate with teams to enhance services through AI/ML solutions.

Lead the design, development, and implementation of machine learning models to solve complex problems, collaborating with cross-functional teams to enhance services and deploy solutions in production environments.

The job involves developing and optimizing machine learning models, overseeing model risk, and collaborating with teams on AI-related projects.

The Principal Machine Learning Engineer leads the deployment of multi-modal AI models on mobile platforms, setting technical vision and optimizing inference performance, while mentoring a team and collaborating cross-functionally.

Lead the development of RL training frameworks and data processing pipelines for AV models, ensuring quality and scaling training workflows.

Lead the development and operationalization of machine learning systems at Taco Bell. Manage a team, optimize models, and ensure performance and reliability in real-time applications.

Seeking a Senior Machine Learning Engineer to design and implement ML systems, optimize deployment, and collaborate with data teams, focusing on scalability and performance.

As a Staff Machine Learning Engineer, you will lead architecture and technical strategy for ML systems, drive multi-functional projects, and mentor engineers while ensuring excellence in ML design and deployment.

As a Staff Machine Learning Engineer at Motional, you'll define ML systems' architecture, lead projects, mentor engineers, and drive technical strategy to optimize data discovery and model improvement for autonomous vehicles.

As a Staff Machine Learning Engineer, lead technical strategy and architecture for ML systems, oversee multi-person projects, establish engineering standards, and mentor team members.

Lead technical strategy and architecture for machine learning systems, mentor engineers, and design scalable solutions for data mining and real-time inference.

The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.

The AI/ML Software Engineer will design, develop, and deploy AI/ML solutions for the Department of War and Intelligence Community, focusing on enhancing operational capabilities and decision-making processes.

Lead the development and deployment of ML models to optimize pricing and enhance customer experiences. Drive AI strategies, conduct research, and collaborate across teams.

Develop and translate advanced ML models for heart disease diagnostics, collaborate with cross-functional teams, conduct research, and manage projects.

Lead development and deployment of end-to-end ML and LLM solutions on Azure (Databricks, AKS) to optimize sales and marketing. Build recommendation, content generation, and RAG-based systems; monitor and improve model performance; collaborate with BI, sales, marketing, and IT to deliver scalable, cost-effective AI solutions.

Conduct applied ML research and develop scalable machine-learning solutions for payment fraud detection. Analyze large datasets, design and deploy models (including graph-based/GNNs), run experiments, optimize algorithms for efficiency, and collaborate with cross-functional teams to integrate models into production systems.

Design, implement, and maintain RAG pipelines and LLM integrations, build embedding generation and retrieval systems, develop REST API integrations, and refine Postgres schemas to support tactical intelligence data workflows in onsite, mission-focused environments.

Design, build, and productionize large-scale batch and real-time ML systems across Content, Pricing & Availability, and Trust & Safety. Lead end-to-end ML projects, establish best practices, mentor junior engineers, and scale solutions for global travel marketplace performance and reliability.

Design and deploy production-grade ML models and pipelines for lane- and route-level semantic/topological mapping. Research and evaluate neural architectures (detection, segmentation, depth, 3D), build data curation/auto-labeling/active learning systems, develop evaluation metrics, and integrate mapping features into the AV fleet through testing, reviews, and collaboration with autonomy teams.

As a Machine Learning Engineer, you will build end-to-end ML systems for autonomous underwriting, collaborating with underwriters and engineers to advance ML capability.

The Machine Learning Engineer will design scalable systems, deploy production ML models, and develop distributed data pipelines, collaborating across teams.