Top Senior Machine Learning Jobs in Salt Lake City, UT

Design the full Search experience across organic and sponsored results, including typeahead, ranking, filters, empty states, and monetization. Establish design principles and components, partner with product, research, data science, and ML engineering, and use experimentation to improve engagement, relevance, and revenue. The role requires substantial search or discovery design experience, strong product craft, consumer instincts, and comfort designing alongside AI and monetization teams.

Leads the technical direction and execution of a machine learning team focused on personalization, relevance, ranking, search, and advertising. Designs, scales, and operates production ML systems, including training, evaluation, deployment, and serving infrastructure. Partners with product, data, and engineering stakeholders, drives architecture and system design decisions, mentors engineers, and uses AI tools to accelerate development and explore LLM-powered features.

Leads Propel America's product and technology strategy, including the Fellow Portal, AI integrations, technology roadmap, software development, Salesforce, infrastructure, data systems, cybersecurity, and vendor relationships. Manages technical staff and outsourced IT providers, oversees architecture, QA, releases, compliance, data privacy, and disaster recovery, and partners cross-functionally to translate organizational needs into scalable products and technology solutions.

Leads enterprise-wide technical and transformation initiatives across Product, Technology, Operations, Data, Security, and Innovation. Responsibilities include program governance, requirements gathering, product documentation, architecture and process modeling, delivery coordination, risk and dependency management, AI use-case evaluation, vendor assessment, and executive stakeholder communication. The role establishes documentation standards and supports modernization through Agile practices, integrations, automation, and responsible AI governance.

Designs and builds data ingestion, feature engineering, analytics, and machine learning pipelines using healthcare and other structured or unstructured data. Develops, tunes, deploys, monitors, and documents predictive models and enterprise data products. Collaborates with data scientists, engineers, product managers, and stakeholders while ensuring data quality, reliability, and production engineering standards.

Develop, train, evaluate, deploy, and monitor machine learning and statistical models using Databricks, Python, SQL, Spark, Delta Lake, and MLflow. Prepare datasets, engineer features, manage model lifecycles, validate data, and support governance practices. Translate client requirements into scalable analytics solutions, analyze trends, and communicate findings to technical and non-technical stakeholders while collaborating across data science, engineering, cloud, security, and business teams.

Senior Commercial Counsel will draft, review, and negotiate complex subscription, partnership, vendor, and other commercial agreements. The role primarily supports a global Sales organization, advises cross-functional teams, manages contracts managers, and handles enterprise and strategic partnership transactions. Responsibilities include balancing competing priorities, supporting legal projects, and providing practical, business-minded legal guidance in a fast-paced environment.

Own audience or measurement products for Fetch’s monetization business, translating advertiser goals and purchase behavior into predictive models, datasets, and causal studies. Build and validate audience expansion, measure advertising outcomes, assess bias and uncertainty, and improve products using campaign results. Partner with Product, Engineering, Sales, and GTM, present findings to customers, and develop reproducible analyses and production-ready assets.

Designs, trains, evaluates, and operationalizes intelligent document-processing solutions using OCR, machine learning, LLMs, Python, and cloud data pipelines. Builds extraction, validation, reconciliation, exception-handling, and human-review workflows for sensitive information. Develops secure, auditable, configuration-driven systems with API integrations, monitoring, testing, CI/CD, and infrastructure as code. Partners with business experts to define document fields, quality thresholds, validation rules, and acceptance criteria.

Lead product vision and roadmap for data and analytics products (ML, generative AI, data pipelines, BI). Translate business needs into developer-ready features, maintain backlog, collaborate with engineering and stakeholders, track KPIs, and drive adoption and continuous improvement.

Leads end-to-end advanced analytics initiatives, including statistical modeling, machine learning, predictive modeling, customer lifetime value, churn, propensity, and segmentation models. Partners with stakeholders to define analytical opportunities, deploy and govern production models, monitor performance, communicate insights to executives, and mentor analysts. Collaborates with data engineering and IT teams to scale analytical infrastructure and champions emerging tools and techniques.

Leads the launch of BGO’s enterprise sales motion for its AI-first data operations proposition. Responsibilities include developing prospecting strategy and sales playbooks, generating new-logo pipeline, selling complex $1M+ enterprise solutions, building executive relationships, closing transformational deals, supporting AI/ML product integration, and representing the company at industry events. The role partners with marketing, communications, client solutions, and leadership on RFPs, product roadmap development, and strategic market initiatives.

Designs, builds, scales, and operates distributed CI/CD services supporting millions of builds, tests, and releases. Develops code for Azure-based infrastructure spanning virtual machines, containers, and custom lab environments. Responsibilities include requirements analysis, architecture and design documentation, estimation, debugging, optimization, operational playbooks, on-call incident response, monitoring, reliability improvements, and mentoring engineers.

Own technical wins for strategic enterprise sales, partnering with Account Executives to discover customer needs and develop production-ready solutions. Build proofs of concept, demonstrations, prototype AI agents, and supporting tools while engaging AI teams, data platform teams, and enterprise architects. Apply hands-on experience with LLMs, agents, data science, machine learning, or data engineering to explain how agents retrieve data and use business context.

Develop and deploy machine learning, statistical, operational research, and semantic analysis solutions for large, complex datasets. Build applied, predictive, and prescriptive analytics; conduct exploratory data analysis; assess and cleanse data; collaborate with software and data engineers to commercialize algorithms; and document and communicate findings to technical teams, stakeholders, and customers.

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.

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.

Leads clinical intelligence initiatives by sizing AI opportunities, conducting data discovery, evaluating AI/ML solution performance, and measuring impact, accuracy, drift, and patient outcomes. Partners with product, clinical, engineering, compliance, and operations teams to develop measurement plans, value hypotheses, benchmarks, and scalable intelligence capabilities. The role is remote with occasional travel and requires advanced SQL, Python, clinical analytics, and population health research expertise.

Develop and deploy AI-driven applications, workflows, integrations, and ServiceNow solutions for enterprise customers. Gather requirements, configure and script ServiceNow modules, implement Now Assist and other AI capabilities, integrate external systems through REST, SOAP, MID Servers, and ETL, and support testing, documentation, deployment, incident remediation, service mapping, and event management. Collaborate with stakeholders and technical leads while maintaining consistent platform patterns.

Owns core backend computation services that produce correct, reproducible, traceable, and auditable financial results. Designs configuration-driven architectures, data-intensive services, and set-based warehouse computations. Requires strong Python, SQL, data modeling, system design, reliability, isolation, and testing expertise. Provides technical leadership through design reviews, engineering standards, and mentorship while partnering with data, AI, and product teams.