Top Machine Learning Jobs in Las Vegas, NV

The role focuses on enhancing detection frameworks using machine learning to identify malicious activities and minimize risks for Netflix.

The role involves developing and optimizing intelligent agents using large language models, collaborating with the team, and solving technical problems.

The role involves building and maintaining ML pipelines, optimizing workflows, and contributing to product strategy with a focus on usability.

The ML Platform Engineer will develop and scale ML infrastructure, automate workflows, and collaborate with data scientists to deploy models efficiently in production.

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 role involves developing ML algorithms for autonomous driving, including training models, evaluating performance, and improving behavioral models.

The Principal Machine Learning Engineer leads the design and implementation of advanced ML systems to enhance cybersecurity capabilities, collaborating with Data Scientists and Engineers.

As an MLOps/ML Platform Engineer, you will build and manage ML systems, optimize workloads, and ensure production model reliability while collaborating across teams.

As a Machine Learning Engineer at Zillow, you will develop and implement machine learning models, prototypes, and algorithms, collaborating closely with scientists and engineers. You will focus on deploying applications, improving reliability, and fostering innovation in AI solutions.

The role involves designing and implementing user-friendly interfaces, collaborating with data scientists on ML model deployment, and maintaining CI/CD pipelines for ML workflows.

The Senior ML Engineer designs and develops advanced machine learning models, collaborates with teams, monitors model performance, and implements MLOps practices for scalability.

The Senior Machine Learning Engineer will build and operate ML systems, manage the model lifecycle, and mentor team members while ensuring sustainability data accuracy.

The Lead Data/ML Engineer will design and maintain scalable data pipelines and AI systems, ensuring data reliability and collaboration with product teams.

The role involves designing and implementing data and AI architectures, developing data pipelines, and integrating machine learning solutions while fostering Agile methodologies and collaboration.

The Senior Product Manager will lead the strategy for an AI assistant, ensuring compliance and user satisfaction while coordinating with cross-functional teams throughout product development.

The Machine Learning Engineer will work on sensing and perception algorithms, deploying computer vision algorithms, and collaborating for code testing and evaluation.

Lead research on humanistic AI for autonomous systems. Collaborate with teams, design experiments, and publish findings in top-tier publications.

As an AI/ML Engineer, you will design, train, and deploy machine learning models, optimize model performance, and collaborate with cross-functional teams to integrate AI capabilities into products.

Lead ML research and development, collaborating with engineers and clinicians to create enterprise-grade products and establish a research agenda while sharing insights through publications and presentations.

The Senior Product Manager will lead the AI-driven product roadmap at Chess.com, focusing on innovative chess tools and deepening user engagement through AI features.

Lead a team of ML engineers and software engineers focused on Ads Content Understanding, driving innovation and efficiency in Ads Monetization.

As a Machine Learning Engineer, you'll develop and deploy ML models for medical imaging, collaborate with teams, and optimize for production environments.

Design and implement ML infrastructure for scalable deployment, collaborate across teams, optimize ML systems, and enhance tooling.

The Staff Software Engineer will lead the design and architecture of the AI/ML platform, mentor engineers, and drive technical direction for MLOps infrastructure in healthcare automation.

Lead the architecture and development of AI and ML features, design evaluation frameworks, and mentor team members to enhance ML-driven product experiences.