Top Machine Learning Jobs in Las Vegas, NV

As an AI Data Annotation Specialist, you will annotate, label, and curate data for machine learning models, ensuring quality and collaboration with a global team.

Lead the machine learning and personalization efforts at Babylist, managing a team focused on enhancing product recommendations, search, and revenue through ML initiatives.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

Lead the design and optimization of programmatic bidding systems, collaborating with engineers and applying analytical methodologies to enhance performance.

As a Software Engineering Intern, you'll develop features for user-facing products, work on API platforms, and design data pipelines while gaining hands-on experience in AI technologies.

The SVP of AI Innovation - Web Scraping will lead the development of AI-driven web scraping strategies, focusing on data acquisition, technology enablement, compliance, team building, and cross-functional collaboration for new data services.

The Product Manager will identify process improvements and innovations, utilize automation and AI, and manage the product lifecycle to enhance productivity and deliver business value.

The Director will lead Macmillan's corporate social media and community growth strategy, enhancing engagement and driving measurable growth across digital platforms through strategic content and analytics.

Lead technical pre-sales engagements, design tailored solutions, demonstrate platform capabilities, assess customer needs, and expand relationships within life sciences and health technology.

As the Data Science Lead for Monetization, you'll shape monetization strategy, lead the data science team, and drive decision-making through measurement and experimentation.

As an Applied Scientist, you will design and implement machine learning models, develop personalized systems, and enhance decision-making through AI technology to improve user experience and business operations.

The Lead Bioinformatics AI Scientist will lead AI and GenAI R&D initiatives to develop advanced clinical testing and genomic data analysis platforms, leveraging expertise in bioinformatics and machine learning.

The Director, Genomics Data will lead genomic data R&D, managing a team to advance data analysis, platform design, and commercialization efforts.

Lead the Opportunity Engine product development, managing cross-functional teams to drive advisor growth and improve client experiences using data and AI.

The Enrollment Advisor helps prospective patients through the onboarding process, providing information and support throughout their enrollment in Revero's program.

The Data Scientist II will enhance marketing strategies through advanced measurement frameworks, statistical models, and cross-functional collaborations to drive revenue growth for Pinterest.

Lead a team of Machine Learning engineers, drive technical direction, oversee large-scale ML systems and improve user experience for over 500M users.

Lead the design and implementation of advanced ML systems at Airbnb, mentoring engineers and shaping concepts into impactful products.

Lead mobile app attribution strategies, collaborating with teams across engineering and data analytics to optimize performance and feature implementation.

Lead the creation and optimization of machine learning algorithms, develop and refine production-grade models, and drive testing of innovative algorithms using historical data.

Develop and implement messaging and positioning for AI products, create marketing content, lead go-to-market strategies, and analyze market research.

Develop and optimize machine learning systems for Yahoo News, collaborate with teams to enhance user experience and editorial tools.

The Software Developer Principal is responsible for architecting and delivering enterprise-grade products on SAP S/4HANA, driving AI adoption, and ensuring scalable, secure solutions while providing technical leadership and mentoring.

Own and close enterprise customer deals, develop expansion opportunities, educate customers on AI architectures, engage with multiple stakeholders, and collaborate with product and engineering teams.

The role involves reviewing AI-generated legal documents, providing structured feedback, and evaluating writing quality to improve AI models used in legal contexts.