Top Remote Machine Learning Jobs in Reno, NV

Lead development of an AI-enabled Ethereum Layer 2 platform: build front-end and back-end systems, deploy and optimize AI models, create data pipelines, collaborate on model training, and contribute to product innovation and other company projects.

Serve as primary post-sales relationship owner for federal customers, driving onboarding, adoption, and retention of HiddenLayer cybersecurity/AI solutions. Coordinate cross-functional teams, conduct business reviews, mitigate risks, capture customer feedback, and support renewals and expansion in complex federal environments.

Sell HiddenLayer's AI security platform to federal agencies by developing account strategies, driving pipeline and revenue, leading technical and executive engagements, navigating federal acquisition and contracting, coordinating cross-functional teams, and supporting adoption, expansion, and renewals across the Intelligence Community, DoD, DHS, and civilian agencies.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

Embed with clients to gather requirements and design AI-driven solutions for fraud and fincrime. Architect, train, evaluate, and deploy custom AI agents and workflows, optimize model performance, establish risk metrics and evaluation pipelines, and collaborate with engineering/product teams to scale into production.

As Software Engineering Manager, you'll lead a team in enhancing content workflows through automation and AI, develop scalable solutions, and manage cross-functional collaboration.

Develop and deploy end-to-end machine learning solutions, collaborate with cross-functional teams, and implement MLOps frameworks while monitoring model performance in production.

The Data Science Actuary role involves building and maintaining rating systems and risk models, conducting analysis for underwriting and operations, and integrating new data sources while collaborating with multiple teams.

The Senior Generative AI Engineer will design and deploy AI/ML solutions, focusing on Generative AI systems and their operational excellence across various sectors like R&D and Clinical Trials.

The GTM role focuses on increasing revenue through new sales and partnerships, understanding client needs, and communicating product value.

Lead post-acquisition member lifecycle strategy and execution across onboarding, activation, engagement, cross-sell, and retention. Architect journeys, build and run automated email/push/SMS programs, define segmentation and measurement frameworks, synthesize analytics for optimization, and champion AI-driven marketing innovations while managing multi-client priorities and mentoring teams.

Lead a team to develop groundbreaking technology combining NLP, big data, and AI to enhance digital communication and interaction.

Build and maintain full-stack product features, backend services, APIs, data pipelines, and AI integrations to transform customer interaction data into AI-powered experiences. Collaborate with cross-functional teams to design, test, and support production systems, internal tools, and user-facing interfaces. Own ambiguous problems end-to-end and raise engineering quality across the data and AI platform.

Lead full-cycle enterprise sales into Fortune 500 retailers, marketplaces, and travel companies. Manage eight-figure deals with C-suite and technical buyers, coordinate internal resources, build procurement-ready ROI/business cases, run pilots/A-B tests, and drive land-and-expand growth while shaping GTM playbooks.

Design, build, and scale low-latency distributed platform components; define technical vision and architecture; collaborate with product and ML teams; evaluate build-vs-buy decisions; prototype research breakthroughs and deliver robust, production-grade services.

Lead healthcare and pharmaceutical marketing analytics: analyze CRM, media, healthcare and behavioral data; build segmentation, attribution, audience scoring, and predictive models; develop measurement frameworks; use Python, SQL, BI and automation; translate insights for executives; mentor juniors and partner with Strategy, Media, and Client Services.

Design, develop, and deliver analytics and BI products on Palantir Foundry integrating Appian and VA financial systems. Build dashboards, data models, and data quality monitoring; translate stakeholder requirements into KPIs and visualizations; support pipeline design, documentation, and training for VA acquisition and financial analytics.

Lead definition and delivery of AI-powered capabilities for a sustainability real-estate data platform. Shape roadmap, partner with customers and data science, own end-to-end features, define evaluation and trust frameworks, and ensure data foundations support AI. Drive cross-functional alignment and use AI tools in product workflow.

Develop, test, and maintain applications using Java, Python, or Node.js. Write clean, efficient code, debug and optimize, collaborate with cross-functional teams, use data structures/algorithms, work with SQL/NoSQL databases, participate in code reviews, and stay current on AI/ML concepts, agents, and automation tools.

Lead and grow the Client Data Science team (including three direct reports); mentor staff; write and optimize R, Python, and SQL code; apply machine learning and statistical methods; aggregate and analyze multi-source data; create visualizations and reports; liaise with stakeholders; document work in JIRA and present findings to diverse audiences.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

The Senior Product Manager will lead the integration of machine learning into search relevance, defining product vision and collaborating with teams to enhance ecommerce search functionality.

As a Sr Director Analyst, you will create actionable research in analytics and AI, advise clients, and lead a team in impactful research. Responsibilities include engaging clients, presenting insights, and mentoring team members in analytics & AI best practices.

As a Data Scientist, you will build predictive models, develop software tools, and analyze geoscientific data to support mineral exploration and discovery.

The Data Scientist will develop predictive models, analyze geophysical data, and collaborate with geoscientists to enhance exploration programs, focusing on mineral deposits.