Top Machine Learning Engineer Jobs

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.

The role involves collaborating with teams to design and develop AI applications, improve tools for analyzing data, and maintain software solutions.

As an Applied ML Software Engineer, you will design and implement ML models, manage cloud infrastructure, and optimize backend systems for AI-driven content discovery and recommendations.

As a Staff Software Engineer in Machine Learning, you will lead projects, develop and deploy machine learning models, and mentor teammates while advancing the autonomy of Saildrone's unmanned surface vehicles.

Lead the design and development of scalable ML infrastructure for autonomous vehicles, enabling efficient model training and deployment. Collaborate across teams to develop and manage automated pipelines and cloud-based systems while focusing on continuous integration and deployment.

Lead the development of AI systems within Unity for game understanding, focusing on innovative machine learning applications and collaboration across teams.

In this role, you will integrate machine learning models into vehicle planning systems, improve decision-making algorithms, and ensure safety and reliability in real-world environments.

The Principal Machine Learning Engineer will lead ML lifecycle projects, developing AI strategies, and implementing advanced machine learning solutions for government clients, while ensuring data integrity and operational efficiency.

The Senior Software Engineer will design and build infrastructure for ML model training and deployment, focusing on AWS technologies, reliability, and collaboration with ML teams.

The role involves developing deep learning models for autonomous driving using imitation and reinforcement learning, and collaborating on machine learning infrastructure and performance analysis.

The role involves improving the data platform for Perception model training, developing APIs, and supporting cross-team integration while mentoring junior engineers.

The Principal Compiler Engineer will lead compiler engineering, optimizing ML model performance and coordinating with development teams to innovate compiler infrastructure.

The Senior Machine Learning Engineer at SmarterDx will deploy, maintain, and optimize machine learning models, collaborating across disciplines to integrate these solutions and improve clinical AI outcomes.

Develop computer vision and machine learning solutions, research algorithms, work with product teams to collect datasets, and balance research with production code.

Develop algorithms using machine learning and statistics to address complex problems. Manage data processing pipelines and deploy solutions on cloud infrastructure.

The role involves bridging machine learning and systems engineering to enhance autonomy performance by optimizing data quality and developing frameworks for synthetic data in autonomous systems.

As a Machine Learning Customer Success Engineer, you will facilitate ML workflows, manage user relationships, and contribute to FiftyOne's development.

The Staff Machine Learning R&D Engineer will innovate machine learning algorithms for spatial computing, collaborate with teams, and translate research into production solutions.

The Machine Learning Annotation Content Developer creates instructional materials for data annotation workflows, developing content for text, image, video, and audio. Responsibilities include producing materials, hands-on exercises, and iterative content revisions while collaborating with the program team to align on learning outcomes.

Develop and maintain scalable ML Runtime components, collaborating with teams to enhance developer efficiency and streamline machine learning processes, while utilizing technologies such as Kubernetes, Docker, and Python.

Design and implement machine learning solutions, improve systems, mentor talent, and collaborate on technical solutions to drive product innovation.

Lead the design and implementation of GPU compute clusters for AI and HPC workloads, managing infrastructure and optimizing performance.