Top Machine Learning Engineer Jobs

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.

The Senior Machine Learning Engineer will design multi-modal vision systems, optimize and deploy models, mentor junior engineers, and improve data strategies for robotic perception tasks.

The role involves developing advanced ML models for scene understanding and managing the end-to-end ML pipeline from data gathering to deployment.

As a Machine Learning Engineer, design imaging algorithms, build acoustic simulations, and develop computer vision systems to enhance brain imaging technology.

As an ML Research Engineer, you'll optimize speech recognition and NLP models, integrate AI components, and develop knowledge graphs. Collaborate with experts, manage rapid experimentation, and publish research.

The Machine Learning Engineer role at Patreon involves developing machine learning models, analyzing data, collaborating across teams, and deploying solutions to enhance creator support.

The Education Engineer will develop educational content on agentic AI, design learning paths, and collaborate with engineers to enhance community understanding of LangChain tools.

The MLOps Engineer will support ML and generative AI initiatives, focusing on automation, security, scalability, and model monitoring across production environments.

Join Artian AI as an AI/ML Engineer to develop their innovative AI platform, focusing on enterprise process automation through agentic AI. Responsibilities include working with AI Workflow Agents, multi-agent systems, and various LLM technologies.

As a Senior Machine Learning Engineer, you will enhance diffusion models, conduct research, collaborate on system implementations, and communicate findings effectively.