Top Machine Learning Engineer Jobs

Design, build, and optimize infrastructure for data and modeling in ML ecosystems, enabling experimentation and development of advanced neural models.

The Senior Machine Learning Engineer will design evaluation frameworks, develop synthetic data pipelines, build evaluation systems, and collaborate with teams to improve model quality in healthcare AI.

As a Senior Software Engineer at NVIDIA, you will design and implement inference software optimizations for AI applications using TensorRT, collaborating with deep learning experts to influence hardware and software design.

The Senior Machine Learning Engineer will design and optimize machine learning pipelines for AI video models, collaborating across functions and translating model performance into business insights.

The role focuses on leading AI/ML architecture and deployment for scalable solutions in cloud security, shaping technical strategies, and managing the lifecycle of AI models.

The Senior Machine Learning Engineer will design, implement, and scale advanced foundation models, collaborate with researchers, and build AI systems. Requires hands-on experience with distributed training pipelines and proficiency in AI frameworks.

The role involves developing and deploying machine learning solutions, optimizing models, and collaborating with cross-functional teams. Responsibilities include cloud architecture, algorithm engineering, and infrastructure best practices.

As a Senior Machine Learning Engineer, you will build and productionize models, develop scalable ML infrastructure, and collaborate with teams to optimize model performance while mentoring others.

The role involves building data infrastructure for ML models, managing petabytes of camera data, and collaborating with cross-functional teams to enhance model quality.

The role involves improving Picture and Audio Quality using Machine Learning, applying advanced techniques to enhance streaming experiences, and collaborating with engineering teams.

The Performance Engineer - Inference will optimize model inference speed and throughput, debug low-level kernel performance, and develop tools to visualize performance data.

Design and implement system-level debugging, validation, and observability platforms. Build automated anomaly detection, visualization and analysis tools, and frameworks for failure classification and regression detection. Extend compilers, runtimes, and instrumentation for advanced profiling. Improve bring-up and low-level debug workflows, partner cross-functionally across hardware, firmware, compiler and runtime teams, lead high-impact initiatives, and support incident response and long-term corrective actions.

Lead integration strategy and execution for Zoox's agentic platform. Collaborate with teams on tool integration, debug failures, and ensure resource readiness for production. Define integration artifacts and contribute to release processes.

Lead training, evaluation, and deployment of ML models for scene understanding and behavior prediction in autonomous vehicles.

You will train, evaluate, and deploy ML models for scene understanding and behavior prediction in autonomous vehicles, while collaborating with engineers.

The Senior ML Operations Engineer is responsible for building and maintaining ML infrastructure, model deployment processes, and collaboration with data teams to optimize predictive modeling solutions.

Design and develop scalable ML infrastructure to support training and inference, optimizing distributed systems, and maintaining operational excellence. Collaborate with various teams to enhance AI capabilities and ensure reliability and performance.

The Sr Engineer, AI/Machine Learning will design and develop AI and ML models for health monitoring devices, analyzing data and collaborating across teams to enhance product capabilities.

The Sr Engineer will develop AI/ML models for health monitoring devices, focusing on algorithm development, data analysis, and cross-functional collaboration.

The AI/Machine Learning Engineer II will design and develop models to analyze data for health monitoring devices, focusing on diagnosis and prediction using various algorithms.

The AI/ML/Data Engineer will design, implement, and deploy production-grade ML systems, build data pipelines, and collaborate with teams to deliver AI solutions across various environments.

As an MLOps/ML Platform Engineer, you will build and manage ML systems, optimize workloads, and ensure production model reliability while collaborating across teams.

The Senior Machine Learning Engineer will design innovative machine learning models for drug discovery, leveraging large-scale single-cell datasets and collaborating with ML Scientists to develop optimized models.

Design and develop scalable, high-performance data and API infrastructure for real-time processing. Mentor engineers and collaborate with teams to enhance AI model evaluations.

As a Senior Machine Learning Engineer, you will develop and deploy ML models for health data analysis, collaborating with cross-functional teams to ensure reliability and regulatory compliance.