Top Machine Learning Engineer Jobs

Design, develop, and deploy machine learning models; analyze large datasets; build scalable data pipelines and distributed computing environments; integrate ML solutions with cross-functional teams; optimize performance and support production ML infrastructure.

The Machine Learning Engineer will design and build systems that improve the AI shopping agent by using real user feedback, focusing on feedback loops and metrics to enhance user interactions and agent performance.

Fine-tune and optimize LLMs (including multi-modal) for humanoid robots and autonomous vehicles; build scalable training and deployment pipelines; work on model efficiency (quantization, weight sharing), synthetic data generation, and cross-team product alignment.

The Machine Learning Engineer II will develop computer vision solutions for defense applications, work on algorithm integration, manage resources, and conduct analyses to improve ML models.

Develop and implement AI solutions, maintain machine learning pipelines, build microservices, collaborate with teams, and ensure model reliability.

Design and build core backend services for a cloud-agnostic ML compute platform. Integrate with GPU hardware and orchestration, improve performance, scalability, reliability, and drive large cross-team initiatives to support ML training and deployment.

The Senior Machine Learning Engineer will lead the development of scalable ML systems, mentor team members, and improve existing data infrastructures while collaborating with various stakeholders to execute strategic initiatives.

Design and build production systems for AI inference, optimize runtime services, and collaborate on AI solutions with researchers and engineers.

Design and optimize recommendation systems using deep learning approaches, manage pipelines and evaluate A/B tests to improve user experiences.

The role involves designing and optimizing recommendation systems for Fortnite's Discover experience, including model implementation and A/B testing.

Design, implement, and deploy machine learning algorithms and scalable ML solutions; collaborate with data scientists, engineers, and federal customers to build analytics capabilities and features; support application deployment and customer enablement.

The Senior AI/ML Engineer will design and develop generative AI applications, ensuring operational efficiency and integration across business functions with a strong focus on AWS and AI/ML technologies.

The role involves applying machine learning techniques to circuit design, analyzing datasets, building and optimizing models, and collaborating with teams on various projects in VLSI and circuit design.

The Senior Computer Vision AI/ML Engineer leads a team to apply AI/ML algorithms in remote sensing, focusing on algorithm deployment and optimization. Responsibilities include data analysis, model training, and technical documentation.

As a Machine Learning Engineer II, you will design, implement, and optimize machine learning models and data pipelines, collaborate with teams, and maintain ML systems in production.

Lead the development and integration of AI and machine learning solutions. Work on large language models and full stack software development for USCYBERCOM.

As a Machine Learning Engineer, you will address AI and robotics challenges, focusing on areas like computer vision, sensor fusion, and predictive modeling.

The AI/ML Engineer will design, build, and maintain AI components and data pipelines, support applied AI use cases, and collaborate with teams to enhance AI and data engineering expertise.

Develop and optimize machine learning models using C++ and CUDA for embedded systems, focusing on latency minimization in AI inference tasks while collaborating with engineers and creating production-ready code.

The Senior AI Ops Engineer will design and deploy scalable AI systems for healthcare automation, focusing on code quality, AI safety, and collaboration across teams.

The Senior Full-Stack Engineer II will lead technical projects, develop AI application services, maintain APIs, and collaborate on system architecture and product design.

The Senior Full-Stack Engineer will lead technical areas, develop AI application services, maintain APIs, collaborate on design, and ship product features.

The Senior Full-Stack Engineer II will lead technical areas, build and scale AI applications, develop APIs and collaborate with cross-functional teams.

The role involves providing technical leadership, building AI application services, maintaining APIs, and collaborating on design and operational excellence with SRE/DevOps teams.

As a Senior Full-Stack Engineer II at DigitalOcean, you'll lead and build AI application services, collaborating on design and operational excellence while maintaining APIs and working with ML platforms.