Top Machine Learning Jobs

Design and develop machine learning models for AI-powered applications while collaborating with teams to achieve business objectives. Responsibilities include data preprocessing, model optimization, mentorship, and infrastructure management.

Design and deploy machine learning models for personalized recommendations and search on Zillow's platforms. Collaborate with cross-functional teams to enhance user experience.

The Senior Machine Learning Engineer will develop and maintain ML infrastructure, deploy models, collaborate with teams, and mentor junior engineers.

The role involves designing Python-based systems for geospatial datasets, deploying ML models, and developing monitoring tools, while collaborating with teams on developer tools in geospatial-AI.

The candidate will design and implement machine learning solutions, collaborate with data teams, optimize models, and ensure production readiness of ML systems.

As a Machine Learning Engineer, you will build and optimize models and systems for protein design, enhancing ML pipelines and infrastructure to support scientists.

Design, implement, and deliver scalable features for Workday's Machine Learning Runtime platform, collaborating with teams to enhance efficiency.

The role involves deploying and optimizing LLMs, designing the ML serving stack, and ensuring high-performance GPU services for production readiness.

The ML Scientist will develop machine learning models for climate risk, collaborate across teams, and validate algorithms to improve predictions of weather extremes.

As a founding Machine Learning Engineer, you will improve core models, optimize LLM inference, develop data pipelines, and ship features directly to users.

The Staff Machine Learning Engineer will lead the development of advanced AI models, collaborate with teams, conduct research, and mentor junior engineers.

The Machine Learning Engineer will design, deploy, and operate ML systems on AWS while ensuring reliability, cost-effectiveness, and compliance for the gaming industry.

As a Machine Learning Engineer, you will build models and agents to accelerate scientific discovery, collaborating with researchers and developing efficient infrastructure.

As a Senior ML Engineer, you'll own ML-driven features from modeling to deployment, drive innovation in generative AI, and mentor junior members.

The Senior Engineer in AI & ML will design and productionalize machine learning models, collaborating with Data Scientists to implement scalable solutions and enhance customer experiences at CarMax.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

The Senior Machine Learning Engineer will enhance recommendation systems, employ AI/LLM technologies, and drive AI innovation for content discovery and user engagement.

The Lead AI & Machine Learning Engineer will develop and industrialize GenAI and machine learning solutions, lead projects, mentor junior members, and improve current ML models within a SaaS framework.

As a Machine Learning Engineer, you will develop and enhance ML methods for 3D object detection and monitor ML systems in production, focusing on real-world applications and optimizing task performance.

Contribute to developing machine learning models for multi-scale biology, focusing on design, deployment and optimization across teams and technologies.

As a Senior ML Engineer at Torc, you will develop and maintain ML frameworks, enabling advanced solutions for autonomous vehicles and improving ML platforms.

Design, develop, and implement machine learning models and collaborate with teams to enhance services with AI/ML solutions.

Design and implement machine learning models, analyze data, deploy ML solutions, and collaborate with teams to enhance products.

The Machine Learning Engineer will design, build, and operate core recommendation systems, innovating ML/AI solutions, collaborating with a tech team, and driving project ideas based on business needs.

The role involves integrating and optimizing machine learning models for autonomous vehicle scenario generation, collaborating on AI-driven safety validation, and contributing to data-driven metrics and tooling.