Top Senior Machine Learning Jobs

The Senior Lead Machine Learning Engineer will design, develop, and implement machine learning systems, collaborating with teams to solve business problems using machine learning applications.

As a Lead Machine Learning Engineer, you'll design, build, and implement ML applications, collaborating with agile teams and focusing on optimizing systems at scale.

The Staff Machine Learning Engineer will lead ML systems design and deployment, mentor engineers, collaborate with teams, and communicate solutions effectively to stakeholders.

Design, develop, and deploy AI/ML solutions for validation processes. Collaborate cross-functionally to enhance firmware and hardware validation efficiency using machine learning analytics.

Lead the design and deployment of machine learning models to detect fraud, collaborating with teams to optimize performance and effectiveness while integrating solutions into existing systems.

Lead development of advanced recommendation systems, driving ML innovation, maintaining ML pipelines, and collaborating across teams to enhance user engagement.

The Lead Machine Learning Engineer designs and implements ML applications, builds data pipelines, collaborates with teams, and ensures performance and governance of ML systems.

Design and implement forecasting and optimization models, build ML pipelines, collaborate with teams for model integration, and improve data workflows.

As a Senior Machine Learning Engineer, you'll design and manage ML infrastructure, work with Data Science to implement models, and oversee system health and reliability.

The Senior Software Engineer will lead technical projects, build AI/ML features, improve APIs, and collaborate on design, ensuring efficient operational practices.

The Senior Software Engineer will provide technical leadership, build and scale AI/ML systems, maintain APIs, and collaborate on design while independently shipping product features.

Lead AI/ML engineering to design, build, and deploy predictive models and reusable ML platforms. Mentor scientists and engineers, collaborate cross-functionally, ensure responsible AI compliance, and publish or patent novel methods. Drive adoption of GenAI/LLM solutions and production-grade pipelines for healthcare use cases.

Lead development of AI/ML solutions for healthcare using structured and unstructured data. Build and test deep learning and classical ML models, design experiments, perform statistical analysis and visualizations, ensure responsible AI compliance, produce documentation/patents/publications, and collaborate on MLOps pipelines and stakeholder integrations.

Design, develop, and deploy production-grade AI/ML models and pipelines (LLMs, RAG, Transformers). Work with agentic frameworks, scale training/inference on Databricks/PySpark, integrate solutions via Docker and REST APIs, leverage cloud services (Azure/AWS), participate in AI governance, and mentor junior engineers to deliver measurable pharmacy optimization outcomes.

As a Senior Machine Learning Engineer, you will build scalable ML systems, lead the ML lifecycle, mentor engineers, and collaborate across teams.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

The Senior AI/ML Engineer will design and implement scalable ML infrastructure solutions, mentor junior engineers, and own key technical projects.

Lead the engineering organization for the Personalization Platform at Capital One, focusing on real-time AI-driven personalization, managing ML infrastructure, and building high-performing teams.

The Senior Machine Learning Engineer will design and implement ML applications, optimize ML models, and collaborate with cross-functional teams to solve business problems using ML.

As a Lead Machine Learning Engineer, you'll design and implement machine learning applications, collaborate with teams, ensure model performance, and build cloud-based infrastructures.

As a Senior Machine Learning Engineer at Capital One, you'll design, build, and deploy ML models, collaborate in Agile teams, and ensure the performance of ML applications. Responsibilities include model training, monitoring, and optimization in cloud-based environments.

Develop and implement machine learning solutions using LLMs, applying fine-tuning and RAG methodologies while utilizing the Langchain framework and ensuring production-quality code.

The Lead Machine Learning Engineer will design, build, and deploy machine learning models and data pipelines, ensuring high performance and governance of ML applications while collaborating in an Agile environment.

Drive technical strategy for the Personalization Platform, develop recommendation systems, maintain ML workflows, and innovate AI solutions for customer engagement.

Develop and scale machine learning systems for physiological signal processing. Design and train models, ensure compliance, and mentor team members while collaborating with cross-functional teams.