Top Machine Learning Jobs

Designs and implements production machine learning solutions within product teams: algorithm and software design, model development, deployment, monitoring, performance tuning, testing, automation, code review, and stakeholder collaboration to meet business requirements.

The Staff Machine Learning Engineer leads the development and deployment of machine learning systems, ensures quality, collaborates with teams, and mentors junior engineers.

Seeking a Principal Software Engineer for architecting ML systems, unifying codebases, and leading cross-team architecture for Waymo's foundation models.

As a Senior/Principal Machine Learning Engineer, you'll design and build core ML systems for Workday's AI agents, collaborating with cross-functional teams on models and deployment for real-world applications.

As an Applied Machine Learning Engineer, develop, deploy, and optimize machine learning models while collaborating with cross-functional teams to enhance customer solutions.

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.

This position involves developing and deploying AI and machine learning solutions, contributing to cross-functional projects, and mentoring junior staff, with a focus on healthcare and insurance applications.

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 build models and agents to accelerate scientific discovery, collaborating with researchers and developing efficient infrastructure.

As an Associate Technical Architect in Machine Learning, you will design and develop advanced ML models on AWS, ensuring scalability and reliability while collaborating with cross-functional teams.

The Machine Learning Engineer will manage AI/ML projects on AWS, optimize data systems and databases, and enhance data architecture for predictive insights.

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 Machine Learning Engineer will build and scale ML infrastructure, drive model performance, and ensure reliability while collaborating with various teams to optimize feature engineering pipelines and champion best practices.

The Staff Machine Learning Engineer will build recommendation systems, lead ML projects, collaborate with teams, and mentor junior engineers, focusing on scalable AI solutions for dating outcomes.

Hinge seeks a Senior Machine Learning Engineer to develop AI-driven dating experiences. Responsibilities include model development, collaboration with teams, and leadership in project execution.

The AI/ML Engineer will design and maintain scalable ML pipelines, collaborate with data scientists, implement containerized workloads, develop APIs, and monitor ML systems.

As a Senior Machine Learning Engineer at Axon, you will develop AI solutions for public safety, collaborate on projects, architect platforms, and ensure ethical AI development.

The Applied Scientist will develop and enhance machine learning models, design A/B tests, evaluate performance, and collaborate with stakeholders to enhance decision-making and operational workflows in healthcare.

The Machine Learning Engineer will design, build, and deploy ML models for data-driven products, collaborating with teams to optimize pipelines and improve performance.

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

Contribute to machine learning projects through development, testing, integration, and support. Collaborate with Data Scientists and adhere to ML best practices.

Develop and deploy ML solutions (LLMs, RAG, NLP, graph ML) at scale: design pipelines, services, and APIs using cloud, Docker/Kubernetes; evaluate, monitor, and lead technical work.

The AI Engineer will design and develop AI-driven solutions, conduct data analysis, build machine learning models, and integrate them within existing systems.

Design and deploy machine learning solutions for credit risk and fraud management, collaborating with stakeholders to optimize model performance and maintain governance of the model lifecycle.

As a Mid AI & ML Engineer, you'll create scalable ML solutions, develop pipelines, work with data, and guide clients on AI strategies.