Top Machine Learning Jobs in Ogden, UT

Lead B2B activation marketing to drive patient starts from commercial referral channels by building scalable systems, attribution frameworks, and repeatable playbooks. Implement MarTech and data-driven strategies, run A/B and incrementality tests, automate campaign execution using AI/ML and LLM tools, and templatize activation campaigns while managing and growing a cross-functional team.

Lead design and implementation of Headway's insurance systems (eligibility, pricing, matching, claims). Build data-intensive, ML-powered platforms and automation, mentor engineers, write high-impact code, and improve accuracy and reliability across state and payer complexity to scale insurance-covered therapy.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

Manage and mentor a global team of data engineers and data scientists, align technical delivery with business goals, allocate resources, improve delivery processes, drive automation and technical evangelism, and collaborate with sales and account teams to support growth.

Develop and validate missile payload models via modeling, simulation, test data processing, and performance analysis. Generate threat models, radar/optical signatures, trajectories, and discrimination algorithms. Support system integration, verification & validation, derive lower-level requirements, create V&V plans/reports, review test plans, and present results to stakeholders.

Lead a team of ML engineers to develop fraud detection models, defining strategies, driving model evolution, and ensuring effective integration with cross-functional teams.

The Senior Product Manager will oversee the strategy and development of telematics data products, manage cross-functional teams, and ensure product viability and market alignment through customer insights and technical fluency.

Design, implement, and test cloud-based ETL/data pipelines and datasets to support analytics and data science workloads. Collaborate with data scientists and analysts, translate business requirements into technical solutions, and follow data engineering best practices.

You will tackle AI challenges, develop scalable software and collaborate with teams to enhance healthcare navigation using AI solutions.

Lead and transform the Fraud Intelligence Team into a high-impact function by improving operating models, QA, tooling, and metrics; build entry-level talent programs; connect labeling to measurable fraud prevention outcomes; deliver actionable insights to Product, R&D, Analytics, and GTM; and leverage AI and automation to increase productivity and business impact.

Partner with functional leaders to translate business strategy into people strategy. Own org design, performance management, compensation, talent development, engagement, and retention. Provide coaching on career pathing, change management, and sensitive employee issues. Use people data to generate insights and recommendations, build compliant HR policies, manage global employee relations, and collaborate with People Team COEs to deliver cohesive people programs at scale.

Serve as second-in-command for Coinbase Derivatives' Market Regulation Department, leading day-to-day regulatory compliance, managing exams and audits, advising on CFTC Core Principles, reviewing surveillance escalations and enforcement actions, and coordinating cross-functional regulatory workstreams to ensure the DCM meets obligations and resolves findings timely.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

Manage a team of software reliability and CBM+ engineers for the Sentinel program. Lead reliability studies, develop CBM+ architecture and prognostic/diagnostic models (physics-based, ML, hybrid), ensure reliability requirements and verification methodologies, plan program performance (cost, schedule, technical), manage staffing and performance, coordinate with design/manufacturing, and support system-level engineering and configuration management under security-controlled program constraints.

Provide legal guidance on Rubrik's AI use and products, ensuring compliance with laws and contracts, drafting and negotiating AI terms, coordinating generative AI review processes, educating employees, and improving AI review controls and workflows across cross-functional teams.

Lead technical direction and deliver large-scale ML platform infrastructure including feature store, model serving, experimentation, and training pipelines. Drive architecture, mentor engineers, coordinate cross-team initiatives, resolve system-wide issues (latency, reliability, GPU utilization), and define safe ML deployment paths from registration through rollout, monitoring, and rollback.

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.

Own the research-to-production pipeline: harden training/evaluation workflows, build packaging/deployment tooling, design release gates, optimize inference and serving for latency/throughput, establish benchmarking and validation, and instrument feedback from production to accelerate research iteration.

Lead enterprise data security architecture to protect sensitive data across its lifecycle. Define strategies for encryption, key management, tokenization, masking, DLP, classification, database security, and Zero Trust. Advise execs and engineering on secure design patterns for data platforms (e.g., Starburst), cloud/on-prem systems, APIs, data pipelines, and AI/ML workloads. Develop roadmaps, evaluate technologies, mentor staff, and drive secure-by-design adoption across the organization.

Lead architecture and design of cybersecurity solutions for federal networks. Identify and implement system hardening, reduce attack surface, and translate IT needs into secure implementation plans. Guide senior leaders, coordinate cross-functional teams, evaluate tools and techniques across IoT, cloud, A&O, IAM, ML, and NGFW, and produce technical documentation, roadmaps, and whitepapers to drive capability maturation.

Leads and manages an applied machine learning team developing fraud detection and identity verification models. Responsibilities include people management, coaching, code review, production ML systems, model lifecycle ownership, experimentation, deployment, monitoring, fraud research, cross-functional prioritization, and communicating results. The role remains hands-on while partnering with Product, Engineering, Risk, and leadership to drive measurable business impact and shape future product strategy using machine learning and AI.

Leads an applied machine learning team and owns fraud detection and identity model strategy, development, deployment, monitoring, and iteration. Partners with Product, Engineering, Risk, and senior leadership to set priorities and deliver business impact. Provides technical mentorship, reviews code, guides modeling and architecture decisions, researches fraud patterns, develops ML capabilities, and shapes responsible AI use under data governance and security constraints.

Own and modernize Apartment List’s B2C lifecycle marketing program across email, push, and SMS. Build segmentation, personalization, partnerships, cross-sell, forecasting, experimentation, and measurement systems. Lead analytics, attribution, deliverability, and revenue optimization while remaining hands-on with journeys, templates, dynamic content, audience logic, SQL, and troubleshooting. Manage a two-person team, partner cross-functionally on roadmap priorities, and oversee the Iterable relationship.

Own strategic enterprise accounts across expansion and new-logo sales motions. Build executive relationships, develop account plans, run account-based outbound, navigate complex buying committees, deliver consultative demonstrations, negotiate contracts, and close high-value SaaS deals. Partner with Customer Success, Business Development, and Marketing while maintaining Salesforce pipeline and forecasts. Success requires consistently meeting quota through longer-cycle, multi-stakeholder deals and contributing to the evolving enterprise sales playbook.

Drive new-account acquisition and cloud migrations for AI and infrastructure solutions. Generate pipeline through global outbound prospecting, execute multichannel outreach, manage the full enterprise sales cycle, and close large cloud, infrastructure, and data center deals. The role requires deep knowledge of AI computing, cloud infrastructure, power capacity, cooling systems, financial modeling, and B2B enterprise net-new cloud sales. Candidates work from Akamai’s San Francisco office and collaborate across time zones.