Top Machine Learning Engineer Jobs

Design and optimize machine learning systems, build scalable data pipelines, and run experiments to improve recommendations for Scribd's products.

As a Senior Machine Learning Engineer, you will create scalable simulation scenarios for autonomous vehicle testing, integrating AI solutions and collaborating with stakeholders.

The ML Software Engineer in Integrity develops algorithms for fraud detection using machine learning, enhances system efficiency, and mentors junior engineers.

The ML Software Engineer will develop and launch machine learning algorithms focused on fraud detection, lead ML project initiatives, and mentor junior engineers while ensuring operational excellence in ML engineering.

The Senior Machine Learning Engineer will design, build, and scale ML models and pipelines, support production efforts, and collaborate with other engineers and data scientists to deliver real business value using AI solutions.

This role involves developing and integrating AI/ML models within GCP using Python, optimizing LLM performance, and applying MLOps practices. Strong collaboration with architects is required for implementation and analysis of workflows.

Develop and optimize ML compilers for high-performance deep learning applications, collaborating with hardware engineers to enhance performance and efficiency while minimizing energy consumption.

As a Research Engineer, you will collaborate on advancing AI systems through reinforcement learning, while contributing to both research and engineering tasks.

Lead the development of AI/ML infrastructure for simulations, optimizing systems for large-scale machine learning models and enhancing realism in autonomous driving.

As a Research-Hardware Codesign Engineer, you'll collaborate across teams to optimize AI silicon designs, implement numeric kernels, and analyze system architectures, driving innovation in AI hardware solutions.

As a Senior ML Infrastructure Engineer, you will design scalable architectures for ML, build robust data pipelines, manage GPU clusters, and drive improvements in CI/CD workflows while collaborating with cross-functional teams.

Build infrastructure for AI/ML environments, collaborate with teams for improvements, and interact with customers to enhance product features.

Develop and optimize machine learning algorithms for LLMs, collaborate on research and engineering solutions, and manage deployment pipelines.

The role involves developing scalable ML solutions, leading cross-functional discussions, analyzing knowledge data, and producing technical documentation to improve search relevance using AI and machine learning technologies.

The role involves designing, developing, and implementing machine learning models while collaborating with teams to enhance services and deploy solutions effectively.

Lead research and development of advanced fraud detection ML models, experiment design, productionizing prototypes, and mentoring engineers.

The AI/ML Ops Engineer will build and maintain CI/CD pipelines for AI/ML applications, containerize models, and ensure deployment in cloud environments. Responsibilities include support for data scientists, security integration, documentation, and client relationship development. The role requires an active Secret clearance and professional experience in cloud environments, programming, and CI/CD tools.

The role involves designing, developing, and deploying machine learning models, especially in NLP, optimizing inference performance, and collaborating with cross-functional teams to enhance solutions.

Design, build, and deploy ML models, develop APIs, optimize AWS workflows, and implement CI/CD pipelines for scalable ML systems.

Lead and manage a team developing ML models for self-driving vehicles, define motion planning projects, and collaborate with cross-functional teams to enhance performance.

The Machine Learning Engineer will develop and deploy large language models focused on preprocessing datasets, training, fine-tuning, and maintaining ML pipelines, primarily in healthcare settings.

Build and optimize infrastructure for private, personal AI models, ensuring performance and privacy while deploying at scale.

Train personalized ML models, create synthetic data pipelines, evaluate model quality, and develop safeguards for AI privacy and misuse.

The Senior Software Engineer will build scalable systems for ML model training and deployment, collaborating with researchers and engineers to improve workflows and ensure efficiency.

As a Senior Machine Learning Engineer, develop solutions for robotic perception, focusing on rare events in warehouses using cutting-edge AI and ML techniques.