Top Machine Learning Jobs in Provo, UT

Designs and builds highly scalable, fault-tolerant Azure compute services, microservices, REST APIs, billing pipelines, and distributed systems. Responsibilities include improving availability, security, scalability, performance, disaster recovery, and compute utilization; using telemetry and data-driven insights; developing cloud-native solutions with containers, NoSQL, and Big Data technologies; and leveraging AI-assisted development in an Agile environment.

Write technically accurate case studies, articles, product explainers, launch materials, and social content for AI engineers, researchers, and technical leaders. Interview customers, partners, and internal experts; learn HUD’s platform and workflows; explain technical products and research clearly; support founder communications; manage content from ideation through publication; and improve content using reader and go-to-market feedback.

Own a new enterprise sales territory, build pipeline from zero, and close advisory-style security software deals with large organizations. Develop relationships with senior security leaders, engineers, and data science teams; tailor sales engagements over lengthy cycles; coordinate demonstrations with pre-sales specialists; and involve company leadership in strategic opportunities. The role requires enterprise security software sales experience, AI and machine learning fluency, startup experience, and proximity to New York City or northern New Jersey.

Product Counsel will advise product, engineering, data science, marketing, compliance, and sales teams throughout the product lifecycle. Responsibilities include counseling on regulatory compliance, privacy, intellectual property, consumer protection, AI and machine learning, data rights, platform architecture, APIs, identity and account security, and marketing. The role translates legal requirements into technical guidance, supports AI governance, monitors evolving laws, and develops scalable legal processes for a fast-paced technology company.

Leads DISCO’s machine learning research strategy, directs advanced algorithm and methodology development, oversees large-scale research programs, and manages research teams. Collaborates with industry partners and cross-functional stakeholders to apply machine learning to real-world challenges. Develops long-term research plans, mentors researchers, optimizes research processes, and contributes to the broader research community through publications, presentations, and industry engagement.

Develops predictive models, machine learning solutions, data pipelines, statistical analyses, and internal data applications. The role uses Python and SQL Server to analyze structured and unstructured data, applying NLP, classification, regression, clustering, automation, and AI/LLM techniques. Responsibilities include maintaining data science platforms, supporting cross-functional decision-making, and communicating technical findings to non-technical audiences.

Develops and deploys production machine learning models and data products for enterprise use. Responsibilities include data mining, feature engineering, model evaluation, NLP and LLM/RAG solutions, API and pipeline integration, cloud-based deployment, model validation, A/B testing, documentation, and lifecycle management. The role translates business needs into scalable data science solutions and collaborates with product, engineering, and business stakeholders throughout the SDLC.

Build end-to-end features for marketing and growth SaaS products, including interactive user interfaces, CRUD applications, backend APIs, analytics platforms, observability tools, and ML integrations. Collaborate with customers, designers, product managers, and ML engineers to translate real-world needs into intuitive products and experiments. Independently architect frontend systems while contributing to backend data models and API design.

Leads financial strategy, planning, forecasting, and operating cadence across Sales, Marketing, Customer Success, and GTM Operations. Owns GTM economics, sales compensation, commissions forecasting, executive reporting, driver-based modeling, resource allocation, and profitability analysis. Modernizes Finance through AI, automation, advanced analytics, improved controls, and scalable processes while developing the GTM Finance team and advising senior executives.

Leads automated scoring and natural language application research for educational assessment products. Responsibilities include setting team priorities, mentoring scientists, designing and analyzing studies, developing machine learning applications, collaborating with stakeholders, presenting technical findings, writing reports, publishing applied research, and supporting products involving automated scoring, crisis-content detection, and formative feedback.

Lead and grow a data science team building production machine learning models. Oversee the full model lifecycle, including data sourcing, feature engineering, training, deployment, and monitoring. Coach technical staff, manage planning and executive communication, investigate fraud patterns, improve model performance, and deliver dependable production code for real-time decisions. Present analyses that guide data strategy, product direction, operations, marketing, and sales.

Leads customer-facing technical delivery from demonstrations and requirements discovery through architecture, implementation, testing, and production launch. Builds AI-driven agents, analytical products, predictive modeling workflows, and data pipelines; integrates solutions with client CRMs, consumer applications, and varied data sources. Partners with client technical teams, presents to senior stakeholders, and feeds field learnings back to the core platform team. Requires occasional travel and strong Python, TypeScript, architecture, cloud, and communication skills.

Leads Aptive’s AI strategy and roadmap while personally delivering production machine-learning systems for forecasting, route optimization, retention, pricing, lead qualification, and customer and technician support. Builds and manages the ML and data science team, partners with data engineering on infrastructure, establishes model deployment and monitoring practices, and oversees responsible AI governance. The role requires measurable business impact, executive-to-engineering communication, and hands-on model and pipeline review.

As a Research Engineer, you'll develop and manage data systems for text-to-speech projects and enhance machine learning models using innovative strategies.

Design, build, and support high-throughput, low-latency LLM inference and data pipelines; collaborate with data scientists to post-train and evaluate models; implement scalable, production-ready systems with strong testing, monitoring, and performance focus; mentor engineers and iterate on architecture, reliability, and user-facing AI applications.

Early-career Data Scientist supporting supply chain transformation through machine learning, forecasting, statistical modeling, data preparation, dashboards, and AI solutions. The role addresses inventory optimization, demand forecasting, production planning, delivery performance, and cost reduction. Responsibilities include developing analytical datasets and workflows with Python and SQL, evaluating models, integrating enterprise data, supporting cloud-based analytics, and communicating insights to business stakeholders in a manufacturing environment.

Own end-to-end SaaS implementations from solution alignment through configuration, data preparation, training, UAT, go-live, and handoff. Serve as the primary customer and project lead, managing timelines, risks, dependencies, stakeholders, and readiness. Configure workflows and platform settings, troubleshoot data and configuration issues, coordinate cross-functional teams, and identify implementation improvements. The role requires strong customer communication, project management, SaaS configuration, data handling, and business workflow analysis skills.

Own the technical sales cycle for Databricks consulting engagements, including discovery, architecture design, solution scoping, estimation, proposals, demos, proofs of concept, workshops, and statements of work. Design lakehouse, data engineering, analytics, governance, security, and AI architectures. Partner with sales, Databricks, alliance, and delivery teams while ensuring effective handoffs into implementation.

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.

Design and deploy production-ready LLM pipelines and agentic workflows, automate large-scale multimodal dataset pipelines, monitor and improve agent performance, and integrate AI agents with 3D scene composition. The role also involves process documentation, incident response, and continuous improvement, with collaboration across the engine team and company founders.

Lead GitLab’s company-wide strategy for autonomous, agentic software development workflows. Identify and validate AI opportunities across the SDLC, build prototypes and reference architectures, establish evaluation frameworks and safety controls, and drive internal adoption. Partner across Engineering, Product, Infrastructure, Security, Architecture, and Data and ML teams to scale reliable, observable, compliant agentic capabilities into customer-facing products. Mentor senior technical leaders and represent GitLab externally on AI-assisted development and productivity measurement.

Leads high-visibility product programs focused on market adoption, analyst relations, customer advisory boards, executive briefings, and industry events. Translates technical product roadmaps into compelling market value propositions, synthesizes analyst and customer feedback, and provides actionable insights to product leadership. Partners cross-functionally with Product, Marketing, and executive stakeholders while supporting strategic initiatives and external-facing communications.

Conducts econometric, causal, statistical, and optimization analyses to improve operational efficiency, resource allocation, product performance, and business outcomes. The role defines efficiency measures, develops forecasting and optimization tools, partners with product and engineering teams on data instrumentation and implementation, and communicates findings to executives through clear reports.

Senior Business Systems Analyst to define requirements for agent-facing servicing applications, design integrations/APIs with core banking systems, translate needs into user stories and acceptance criteria, improve agent workflows and productivity, and identify AI/ML opportunities for fraud detection, automation, and operational analytics. Supports testing, validation, and releases.

Build and deploy mechanistic, hybrid, and data-driven models for pharmaceutical CMC processes, including drug substance, drug product, packaging, labeling, technology transfer, and manufacturing. Integrate process and experimental data into FAIR data products, analytics, dashboards, and AI-enabled tools. Partner with technical teams and CDMOs to support process understanding, forecasting, risk assessment, regulatory filings, and technology-transfer decisions while owning the digital roadmap and mentoring colleagues.