Top Senior Machine Learning Jobs in Provo, UT

Design, develop, and evaluate conversational AI agents and generative AI products. Collaborate with AI scientists, ML engineers, and Responsible AI/Model Validation teams to ensure state-of-the-art, ethical solutions and support deployment and integration of conversational systems.

As the Engineering Lead, you will guide product strategy, manage and mentor engineers, and ensure successful execution in product areas, focusing on machine learning and technical expertise across teams.

The Hyperscalers and Commercial Lead will develop technology-driven business strategies, drive customer adoption, and manage end-to-end sales processes while working closely with cross-functional teams.

Design, build, and operate production AI platform capabilities and agentic workflows. Collaborate on architecture, write production-quality backend code, mentor developers, troubleshoot production issues, and drive adoption of reusable AI frameworks, MLOps practices, and cloud-native intelligent services across a multi-tenant SaaS dental platform.

The role involves researching, developing, and implementing AI solutions, optimizing models, integrating AI into workflows, and collaborating with teams to enhance business efficiency.

Lead pre-sales technical engagements for Conversational and Generative AI solutions, collaborate across teams, and design value-driven demos for enterprise customers.

The Principal Architect will lead AI/ML solutions, mentor teams, and collaborate with clients to design and deliver scalable systems using Google Cloud technologies, ensuring compliance with ethical standards.

The Data Science Manager will lead and mentor a team of data scientists, drive data-driven decision-making across Stripe, and collaborate with various stakeholders. Responsibilities include managing projects, recruiting, and contributing to broader data science initiatives.

The Senior Display Media Account Manager develops and executes digital media strategies, focusing primarily on Amazon DSP, while fostering client relationships, providing analytics, and driving business growth for clients.

As a Senior Data Scientist, you will apply machine learning and AI algorithms, conduct feature engineering, and collaborate with teams to optimize models and provide data insights.

Lead the design, development, and deployment of scalable machine learning and AI systems for enterprise clients, guiding architecture and mentoring engineers.

Lead the architecture, implementation, integration, and optimization of Oracle EPM Planning solutions. Design planning, budgeting, forecasting, modeling, security, metadata, and reporting frameworks; configure Oracle EPM modules; and apply AI-driven forecasting capabilities. Lead requirements workshops, testing, deployment, stakeholder presentations, and pre-sales activities. Mentor consultants and developers while advising finance and executive stakeholders on enterprise planning transformation initiatives.

Design, build, and deploy production-grade ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM applications, and scalable data pipelines with observability and MLOps practices for cloud and on-prem environments.

Design, build, and deploy production ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM features, data pipelines, observability, MLOps, and containerized deployments across cloud and on-prem environments.

The Senior Machine Learning Researcher will design experiments, research new algorithms, and collaborate on deploying models for computer vision and robotics applications.

Leads enterprise sales strategy and revenue growth for AI-powered eDiscovery, legal technology, compliance, analytics, and data intelligence solutions. Builds pipelines, manages complex consultative sales cycles, develops executive client relationships, expands strategic accounts, and positions responsible AI adoption. Partners with product, operations, legal, security, marketing, and executive teams on solution development, pricing, contracts, implementation, and market expansion across corporations, law firms, government, and regulated industries.

As an AI Applications Engineer, you will bridge AI research and implementation, driving experiments, building infrastructure, and releasing products to improve user experience and metrics.

Leads technical solution development for military and federal health capture and proposal efforts. Designs secure cloud, DevSecOps, EHR modernization, interoperability, data, and analytics architectures; develops technical volumes, graphics, compliance matrices, staffing estimates, demonstrations, and presentations. Ensures security and compliance alignment, supports pricing strategy, collaborates across capture and delivery teams, and mentors architects and subject-matter experts.

Oversee development, validation, monitoring, and governance of consumer credit risk models used for loss forecasting, credit decisioning, regulatory reporting, and risk management. Apply statistical, econometric, and machine learning methods to PD, LGD, and EAD models; support CECL, stress testing, and macroeconomic scenario analysis. Assess model performance, data quality, and compliance while communicating findings to senior leaders, auditors, regulators, and other stakeholders.

Leads strategy, roadmap, development, and adoption of analytics and AI products for Ford Integrated Services. Owns reporting platforms, dashboards, governance, metrics, support models, and generative AI initiatives. Partners with senior stakeholders and cross-functional teams including engineering, design, data science, and analytics to deliver actionable insights, improve subscriptions performance, and establish trusted business intelligence solutions.

Lead and grow a data science team focused on customer intelligence, personalization, product analytics, marketing optimization, and customer lifetime value. Develop predictive and segmentation models, analyze web and mobile engagement, design experimentation programs, and apply causal inference, survival analysis, forecasting, Bayesian methods, NLP, and machine learning. Partner with Product, Marketing, Editorial, Data Operations, and Engineering to translate customer behavior into scalable products, actionable recommendations, and measurable business impact.

Lead Elastic’s strategy, vision, and multi-quarter roadmap for vector databases, embedding and reranking models, vector indexing, semantic ingestion, and search capabilities. Conduct market and competitive research, define product metrics, prioritize features, and partner closely with engineering, cloud, and applied research teams. Guide technical trade-offs involving recall, latency, index size, ingestion throughput, model lifecycle, and total cost of ownership across serverless and self-managed deployments.

Owns a portfolio of Data-as-a-Service products end to end, including vision, roadmap, requirements, agile delivery, pricing, packaging, distribution, privacy compliance, and go-to-market execution. Partners with engineering, data science, legal, marketing, sales, and customer success to deliver data enrichment, identity, and audience products through APIs, clean rooms, marketplaces, integrations, and self-service channels. Uses launch metrics and customer insights to guide investment decisions.

Own the end-to-end rebuild of Nextdoor’s consumer search experience, including query understanding, retrieval, ranking, result quality, organic and sponsored content blending, and monetization. Define search relevance metrics, partner with engineering, data science, ML, research, design, and marketing teams, and use A/B testing to improve engagement and revenue while protecting user experience.

Leads commercial, privacy, and product legal functions for a cloud technology company. Drafts and negotiates complex SaaS, partnership, reseller, and technology agreements; advises on global privacy, data protection, AI, intellectual property, and product development issues; develops contracting processes and playbooks; partners with cross-functional teams; and manages, mentors, and develops legal professionals.