Top Remote Machine Learning Jobs in Salt Lake City, UT

Leads Stitch Fix’s Product Algorithms portfolio across Growth, Styling, and Fix & Freestyle. Defines strategy and roadmaps for machine learning, AI, experimentation, personalization, and product analytics; drives scalable production capabilities and measurable business outcomes; improves planning, operational readiness, incident management, and decision-making; and builds a high-performing organization of managers and senior technical contributors while partnering with executive and cross-functional stakeholders.

Own the strategy, requirements, evaluation, and execution of AI agent products and systems. Partner closely with ML, backend, and mobile engineers to make trade-offs across quality, latency, cost, reliability, and user experience. Define evaluation frameworks, drive prioritization, and ensure AI features are understandable, predictable, safe, and trusted. Translate model capabilities and feedback into product decisions and reliable real-world workflows.

Own the strategy, requirements, evaluation, and reliability of AI agent products. Partner closely with ML, backend, and mobile engineers to make trade-offs across quality, latency, cost, reliability, and user experience. Define offline and online evaluation frameworks, drive product execution, and ensure AI features are correct, predictable, safe, and trusted. Translate model capabilities and feedback into product decisions, roadmaps, and rapid iteration.

The Senior Product Architect will design security products, collaborating with product management and engineering teams, focusing on architecture and functionality for high-level product features.

Lead the Data Sources product roadmap for document parsing, fraud detection, and bank aggregation. Drive metrics (parse accuracy, fraud catch rate, connection success, SLAs), write specs, engage clients, mentor PMs/engineers, and represent the platform externally. Prioritize document types, extraction models, reliability, and scalability to improve conversion, client satisfaction, and operational efficiency across mortgage, tenant screening, and government use cases.

Lead enterprise AI and transformation engagements—own customer relationships, scope buildable solutions with FDE, drive commercial outcomes and expansion, advise C-suite on AI strategy, and create repeatable, scalable offerings to evolve Tive into an AI-powered intelligence platform.

Senior individual-contributor role leading 3Cloud's enterprise AI strategy and Center of Excellence. Advise C-suite clients, define AI architectures and standards, drive adoption, develop offerings, and convert strategy into implementation while mentoring technical leaders and shaping commercial growth.

Lead Pearl's Enterprise AI product business end-to-end: define vision and GTM, build and scale AI+human offerings, partner with enterprise customers, and run a lean cross-functional team to deliver measurable commercial outcomes.

Leads enterprise strategy, development, and adoption of applied AI, data science, and commercial intelligence capabilities. Oversees multidisciplinary teams, AI-powered products, scalable data and AI platforms, governance, model lifecycle management, and responsible AI practices. Partners with commercial and technology leaders to prioritize use cases, drive measurable ROI, build talent, and accelerate business growth, customer engagement, operational efficiency, and data-driven decision-making across a regulated, life sciences environment.

Lead integrated paid media strategy and execution across channels, modernize media planning with technology and data, manage agency/vendor relationships and multimillion-dollar budgets, build media capabilities and teams, and deliver executive insights to optimize ROI using AI, automation, and advanced measurement.

Lead discovery, definition, and delivery of B2B SaaS product features. Own customer research, data-driven prioritization, UX collaboration, KPI tracking, and cross-functional execution with engineering, marketing, and customer success.

The Staff Technical Program Manager will manage robotics projects, oversee cross-functional teams, ensure timely delivery, and maintain effective communication across stakeholders.

Lead AI risk assessments, reviews, and monitoring to support AI governance at a financial institution. Evaluate internal and third-party AI solutions, maintain an enterprise AI inventory, analyze controls and risk metrics, build dashboards and reports, and provide quantitative and advisory support across stakeholders to enable responsible AI adoption and regulatory readiness.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Lead a centralized Data Science & Engineering team to build scalable data pipelines, productionize ML/AI solutions, ensure data governance and reliability, partner with cross-functional stakeholders to prioritize initiatives, and drive platform improvements for analytics, personalization, and product features.

Drive pricing analytics, margin optimization, competitive intelligence, and AI adoption across Commercial Management. Develop pricing models, predictive analytics, AI-assisted recommendations, dashboards, and executive reporting to improve profitability, forecasting, governance, and commercial decisions. Automate reporting and workflows, monitor competitor and deal intelligence, identify margin leakage and growth opportunities, and present actionable insights to senior leadership.

Provides strategic and technical leadership for Lilly’s eDiscovery program across the full EDRM lifecycle. Manages legal hold systems, data preservation and collection, processing, review, production, vendor relationships, workflows, and chain-of-custody requirements. Evaluates AI, machine learning, TAR/CAL, predictive coding, and analytics solutions while ensuring defensible legal processes. Partners with Legal, Privacy, Records Management, IT, Compliance, Cybersecurity, outside counsel, and business stakeholders, and mentors team members.

Lead technical pre-sales engagement: present Snowflake to executives and engineers, deliver demos and enterprise proofs-of-concept, design solutions, map customer architectures to Snowflake, collaborate with product and engineering, and close large deals while maintaining deep ML/generative AI and data platform expertise. Approximately 30% travel.

The Director will lead Macmillan's corporate social media and community growth strategy, enhancing engagement and driving measurable growth across digital platforms through strategic content and analytics.

Build and deploy machine learning models on large healthcare datasets, extract actionable insights, develop scalable data processing systems, collaborate with cross-functional teams, and communicate findings to stakeholders to improve patient outcomes.

The AI Application Engineer will design and deploy AI systems, collaborate with teams, implement Generative AI solutions, and promote continuous learning in AI practices.

Own the technical side of deal progression for airline deployments: qualify opportunities, run demos and POCs, author integration and deployment architectures (PSS, APIs, data feeds, DNS, identity, networking), respond to RFPs/security questionnaires, scope SOWs and NFRs, and build reusable demo/reference assets to drive adoption and expansion while liaising between sales, engineering, and customers.

The Enterprise Account Executive will drive revenue growth by managing complex sales cycles, closing deals with Fortune 500 companies, and understanding both technical and business needs.

You will execute and improve insurance workflows, analyze operational efficiency, collaborate with product teams, and support onboarding and documentation efforts.

Lead end-to-end ML systems for identity verification, including document authenticity, face match, liveness and deepfake detection. Build GNN-based identity graphs, behavioral/device-intelligence models, vendor benchmarking/evaluation, and production enforcement. Mentor engineers and align ML architecture with Product, Compliance, Risk, and Security stakeholders.