Top Senior Machine Learning Jobs in Provo, UT

Owns product strategy, roadmaps, prioritization, discovery, and delivery for software, data, and AI products supporting behavioral healthcare. Partners with engineering, clinical, community, operations, and executive teams to translate care models into workflows and product features. Leads user research, experimentation, analytics, and field pilots to improve care delivery and outcomes.

Develop and implement data science strategies for machine learning applications including lead scoring, churn modeling, pricing, personalization, and fraud detection. Own end-to-end initiatives spanning data analysis, feature engineering, model training, inference, and monitoring. Collaborate with engineering, infrastructure, analytics, and business teams to deliver measurable impact, improve data capabilities, and communicate findings to technical and non-technical stakeholders.

Build scalable systems and machine learning models that transform satellite imagery into labeled geospatial data and production computer vision products. Responsibilities include developing data and annotation pipelines, tracking lineage and versioning, deploying inference services, evaluating models, supporting cloud infrastructure, and improving labeling workflows. The role requires strong Python, cloud, containerization, CI/CD, infrastructure-as-code, production support, and deep learning expertise, with preferred experience in GCP, Vertex AI, spatial databases, and satellite imagery.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Own the strategy, roadmap, requirements, launch, adoption, and success metrics for a technical platform. Partner with engineering, data, product, and business teams; evaluate architecture, APIs, and system tradeoffs; prioritize foundational investments against customer and revenue outcomes; and apply AI to improve platform capabilities. The role requires strong product management experience, technical depth, analytical skills, and production experience with LLM-based or ML-adjacent products.

Lead the In-Vehicle Experience team at Samsara, focusing on transforming in-cab cameras into intelligent companions. Collaborate with engineering, prioritize features, and ensure client interactions highlight trust and connection. Conduct customer research and integrate AI and ML into product features.

Develop and optimize full-funnel, multi-channel demand generation campaigns that generate pipeline, accelerate deals, and support cross-sell and upsell opportunities. Partner with product marketing, sales development, content, product, field, partner marketing, and analytics teams. Build lead-nurturing programs, align assets to buyer stages, monitor conversion and ROI metrics, and create dashboards to optimize campaign performance.

Lead go-to-market strategy for Sprout Social’s AI portfolio, including the Trellis AI agent. Develop enterprise launch playbooks, positioning, executive messaging, campaigns, and enablement programs. Analyze market and competitive dynamics, influence product roadmaps, improve launch processes, and partner with Product, Sales, Revenue, Brand, and executive leadership to drive adoption, revenue growth, deal expansion, and category leadership. The role also mentors marketing team members and operates with substantial autonomy.

Leads the Category Market Insights team, developing category, consumer, competitive, and portfolio intelligence to guide commercial strategy. Synthesizes data, conducts qualitative and quantitative research, creates dashboards and research repositories, monitors competitors and trends, presents insights to executives, and translates business questions into actionable research plans. The role also develops team capabilities and applies advanced analytics, including ML and AI, to business questions.

Lead agile design and development projects for mobile apps and digital products. Coordinate product, design, engineering, marketing, leadership, and client stakeholders; manage project plans, scope, requirements, backlogs, acceptance criteria, deadlines, workflows, and deliverables. Support scoping and client relationship management while ensuring successful end-to-end software launches and alignment with business objectives.

Develop and operate production ML and AI systems powering patient experiences such as matching, ranking, recommendations, onboarding, and personalization. Build reusable ML infrastructure, pipelines, evaluation, observability, and model-serving capabilities. Provide technical leadership across the ML lifecycle, guide architecture, evaluate custom versus foundation-model approaches, and partner with ML and Patient Engineering teams to deliver reliable, scalable AI products.

Leads the AI Engineering team across applied AI features and foundational ML infrastructure. Responsibilities include managing Senior and Staff engineers, hiring and coaching, deploying LLM-powered capabilities, building MLOps and AI observability platforms, balancing product delivery with platform investment, and ensuring privacy, compliance, evaluation rigor, and clinical safety in production systems.

Own the strategic vision and roadmap for Coursera’s AI-driven search experience. Lead conversational search, personalization, semantic and multilingual search, ranking, and discovery improvements. Partner with engineering, design, research, data science, ML, marketing, and partnerships teams to deliver scalable platform capabilities. Use experimentation, market analysis, KPIs, and customer insights to improve conversion, merchandising, learner experience, and revenue.

Set the technical vision for data science, lead complex statistical and machine learning model development from concept through production, and architect scalable modeling platforms and pipelines. Develop credit risk, pricing, and loss forecasting models; establish model governance standards; partner with senior leaders; mentor data scientists; and communicate technical strategy to executives. The role emphasizes production deployment, monitoring, cloud architecture, and high-impact decision-making across the business.

Develop and maintain production machine learning models, build scalable training and serving technologies, optimize real-time and batch ML pipelines, and monitor model performance and drift. The role involves deep neural networks, recommendation systems, automated retraining, ML research, engineering excellence, and communicating technical concepts to diverse audiences. Candidates need 6+ years of industry ML experience, strong coding skills, and experience deploying neural networks at scale.

Leads Pattern’s organic growth and conversion strategy across SEO, GEO, and AEO. Owns AI-driven search visibility, technical SEO, CRO, landing-page optimization, A/B testing, analytics, reporting, and organic growth forecasting. Coordinates cross-functional initiatives with product, UX, content, engineering, brand, and paid media teams while building scalable systems and translating performance insights into leadership recommendations.

Serve as primary client contact for a portfolio of loyalty-program clients. Scope and manage end-to-end actuarial analyses rooted in predictive modeling and machine learning, validate model outputs, translate results into clear recommendations and presentations, and partner with analysts and data scientists to deliver high-quality, client-facing work in a fully remote consulting environment.

Leads cyber risk assurance strategy and multidisciplinary teams responsible for control monitoring, testing, evidence management, issue remediation, audit support, regulatory readiness, and assurance automation. The role advances continuous, AI-enabled assurance by translating regulatory and cybersecurity requirements into measurable outcomes, maintaining assurance frameworks, evaluating control effectiveness, managing concurrent activities, and reporting metrics to support executive risk decisions.

Own and negotiate complex commercial transactions, including customer agreements, research collaborations, partnerships, data licenses, SaaS contracts, vendor agreements, and professional services agreements. Partner with sales, science, finance, and R&D teams, particularly on life sciences and computational chemistry deals. Build scalable legal infrastructure through playbooks, templates, fallback positions, self-service processes, and AI-enabled contract workflows.

Leads go-to-market strategy and product marketing for emerging AI products in the defense market. Responsibilities include positioning, messaging, launch planning, technical content, demonstrations, market research, competitive analysis, product evangelism, and cross-functional collaboration with Product, Engineering, Growth, and executive teams. The role translates complex technical capabilities into customer value and supports product adoption in new or undefined markets.

Leads technical product marketing strategy for UDS Fleet, including positioning, messaging, go-to-market planning, launches, adoption, market research, competitive analysis, technical content, demonstrations, and sales enablement. Partners with Product, Engineering, Growth, and leadership to communicate the value of edge, distributed, and secure software deployment capabilities across defense environments. Serves as a product evangelist and translates complex technical concepts into customer-focused narratives.

Designs AI-driven user experiences by leading requirements workshops, product discovery, user research, and hypothesis validation. Creates workflows, storyboards, wireframes, journey maps, and intuitive interfaces for complex AI functionality. Collaborates with stakeholders, clients, and development teams to define requirements, prioritize opportunities, communicate design decisions, and deliver user-centered solutions.

Leads technical enablement and sales success for strategic national channel partners. Aligns partner and company go-to-market strategies, develops business plans, conducts technical and sales training, supports evaluations and configurations, and serves as a trusted technical advisor throughout the sales cycle. Builds executive relationships, coordinates training and marketing activities, gathers partner requirements, mentors technical managers, and collaborates with sales, systems engineering, and channel teams.

Leads strategy, roadmaps, backlogs, discovery, delivery, and continuous improvement for AI-powered products. Partners with engineering, AI/ML, data, design, and business teams to translate customer needs into measurable solutions using generative AI, LLMs, agents, and automation. Manages stakeholders, product metrics, responsible AI considerations, and complex consulting engagements, including PMO and multi-team delivery responsibilities.

Coordinates data platform incident response, triage, escalation, root cause analysis, problem management, post-incident reviews, and operational improvements. Maintains runbooks, documentation, metrics, dashboards, and stakeholder communications. Implements and monitors security controls, supports security incident response, vulnerability remediation, compliance audits, regulatory reporting, disaster recovery exercises, and cross-functional coordination across data, cloud, infrastructure, DevSecOps, application, and governance teams.