Top Machine Learning Jobs in Salt Lake City, UT

Lead mainframe modernization and migration architecture for large global clients. Conduct discovery workshops, assess legacy environments, develop transformation and re-platforming solutions, present technical business cases, and advise executives. Partner with sales, consulting, operations, product management, and clients to create solutions, influence technology roadmaps, drive stability and innovation, and support complex opportunities. The role requires deep mainframe expertise across legacy languages, databases, operating systems, infrastructure, and modernization technologies.

Leads the full lifecycle of clinical NGS diagnostic algorithms for oncology and liquid biopsy applications. Responsibilities include algorithm design, analytical validation, design control, regulatory readiness, variant calling, QC metric development, probabilistic modeling, machine learning, and validation pipeline automation. The role serves as technical authority for algorithm changes, supports regulatory submissions, and develops solutions for low-input, fragmented, and ultra-low-frequency genomic variants.

Leads enterprise evaluation, governance, and implementation planning for emerging mental health therapeutics, including digital therapeutics, AI-enabled tools, neuromodulation, pharmacotherapies, and technology-enabled care models. Develops clinical protocols, workflows, provider training, safety criteria, outcome measurement, and adoption support. Partners with clinical, technology, research, quality, operations, and growth teams; evaluates vendors and evidence; monitors regulatory developments; and advances responsible innovation across the organization.

Lead end-to-end data science and AI projects: translate business problems, prepare large datasets, build and deploy predictive/prescriptive and generative AI models (including LLM fine-tuning and prompt engineering), communicate insights to stakeholders, and promote responsible, explainable AI practices across consulting engagements.

Design and deploy production machine learning models and conversational AI agents that transform advertiser briefs into optimized media plans. Build evaluation systems to improve model and agent quality, collaborate across science and engineering teams, investigate ambiguous problems, and iterate using performance data and seller feedback. Communicate effectively with technical and non-technical stakeholders while contributing broadly across machine learning domains.

Leads end-to-end customer onboarding and implementation programs, translating customer goals into project plans, milestones, dependencies, risks, and success metrics. Coordinates Sales, Product, Engineering, Support, Customer Success, trainers, and subject-matter experts without performing hands-on technical implementation or training. Establishes scalable operational frameworks, manages cross-functional accountability, oversees technical readiness, tracks adoption, facilitates stakeholder communications, and ensures customers are prepared for go-live.

Own the strategy and roadmap for Constructor’s search quality and Product Discovery Engine. Drive measurable improvements in relevance, conversion, revenue per visit, and GMV across retail verticals. Partner with ML, data science, and engineering teams to productionize state-of-the-art retrieval, ranking, query understanding, personalization, and LLM capabilities. Establish evaluation frameworks, investigate quality issues, align multiple teams, and expand into chapter-wide product leadership.

Lead the design, development, testing, deployment, and productization of scalable AI/ML solutions. Build and optimize machine learning and deep learning models, transform prototypes into secure enterprise systems, and develop production-grade MLOps pipelines and CI/CD workflows. Guide AI/ML strategy, roadmaps, cloud deployments, and enterprise integration while mentoring engineering teams, advising customers, supporting workforce planning, and collaborating with technical and government stakeholders.

Own the full sales cycle across North America, including prospecting, pipeline generation, client meetings, contract negotiation, and closing new business. Build markets across eCommerce, fintech, real-money gaming, and mobile apps while partnering with Customer Success, Marketing, and Product. Represent the company at industry events, monitor mobile advertising trends, and achieve personal and regional revenue targets exceeding $1 million annually.

Own end-to-end client relationships for a book of B2B SaaS customers: drive adoption, engagement, retention, and expansion of AI-powered contract drafting tools. Lead onboarding, training, large-scale rollouts, and translate customer feedback into product improvements while designing scalable CS processes and tracking health metrics to demonstrate value.

Own lifecycle marketing performance across patient onboarding, activation, early care, and retention. Design and analyze multichannel experiments, build reporting and dashboards, write SQL, diagnose funnel and segment performance, and integrate AI and machine learning signals into lifecycle journeys. Collaborate with Product, Operations, Data Engineering, Marketing Operations, Analytics, and Creative to improve patient outcomes and measurable business performance.

Lead the design and development of Azure Compute Fleet capabilities that orchestrate Virtual Machine Scale Sets across regions. Build distributed control-plane services, APIs, and workflows for capacity placement, scaling, failover, and lifecycle management. Collaborate across Azure engineering teams, drive AI-enabled engineering improvements, participate in on-call operations, and improve reliability, observability, performance, and recovery for hyperscale cloud services.

Lead the roadmap and delivery of an AI-native L1 IT operations agent. Partner with customers, design partners, engineering, and go-to-market teams to ship enterprise-scale capabilities, improve self-service adoption, and build trust through transparent agent experiences and feedback loops. Drive product strategy from discovery through launch in a fast-paced, ambiguous environment.

Build data foundations and end-to-end pipelines, research and implement quantitative pricing, market-making, and risk models for prediction markets, model cross-market dependencies and parlays, develop backtesting/simulation frameworks, monitor model performance and collaborate closely with traders to improve pricing and trading outcomes.

Entry-level Software Engineer on the Applied AI team, building production applications and infrastructure supporting machine learning, analytics, credit decisioning, pricing, and risk systems. Responsibilities include writing tested and documented Python code, collaborating with ML and Analytics teams, learning production deployment practices, communicating technical decisions, and using AI-assisted coding tools.

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 a cross-functional team to develop medical coding software and improve a chart confidence pipeline. Translate stakeholder requirements, guide data scientists and engineers, evaluate recommendations, and report progress to internal stakeholders to increase automation and chart readiness.

Develop and deploy LLM and machine learning models for Airbnb Community Support. Responsibilities include automating LLM evaluation, curating synthetic datasets, analyzing customer issues, identifying model failure modes, building personalization models, exploring data, prototyping solutions, and communicating insights to cross-functional stakeholders. The role focuses on scalable, production-ready AI products and operational optimization.

Leads the AI product strategy and roadmap, extending governed Alteryx workflows and business logic into enterprise AI agents and LLM ecosystems. Owns the Faster, Better, Cheaper ROI narrative, benchmarks product performance, quantifies customer value, champions trustworthy AI through the VURA framework, and represents the product vision with customers, analysts, and external audiences.

Own the enterprise architecture vision for scalable, high-performance, cost-efficient multi-tenant SaaS systems. Lead AWS cloud optimization, distributed data and AI infrastructure, architectural governance, and Architecture Review Council activities. Guide engineering teams on microservices, event-driven systems, automation, and cloud-native practices while driving GenAI adoption across the software lifecycle. Build prototypes, establish architectural standards, optimize total cost of ownership, and mentor technical leaders.

Leads Dandelion Health’s AI developer business by building pipeline, closing clinical AI data and validation partnerships, recruiting developers into its marketplace, and achieving revenue targets. Develops commercial strategy, manages executive relationships, structures agreements, and collaborates with marketing, product, data, engineering, and clinical informatics teams. Represents the company at industry events and advises on clinical AI validation, regulatory, payer, and competitive dynamics.

Researches, develops, tests, and maintains materials-aware machine learning models and software. Designs scalable ML systems, improves model interpretability and uncertainty quantification, and develops inverse-design capabilities. Collaborates with product, engineering, and external research teams to deliver customer-focused AI solutions, publishes research, reviews code, analyzes model performance, and mentors developers.

Develop and deploy machine learning algorithms that improve real-time device identification and fraud detection. Own data science projects from experimentation through production, including supervised, semi-supervised, and unsupervised learning, real-time inference, training automation, exploratory analysis, and model-to-service integration. Contribute to engineering best practices, collaborate within a global remote team, and participate in a shared on-call rotation.

Improve 1Password’s technical SEO across consumer, PLG, and enterprise websites. Responsibilities include diagnosing and resolving crawlability, indexing, rendering, performance, structured data, internal linking, and international SEO issues; implementing CMS changes; partnering with engineering on requirements and release QA; leading migration workstreams; and building monitoring, dashboards, automation, and repeatable processes using search, analytics, crawl, log, and CMS data.

Own product strategy and delivery for agentic document management, policy and procedure workflows, and compliance gap assessments. Partner with customers, design, engineering, and go-to-market teams to build reliable, explainable AI experiences that accelerate audit readiness and security program expansion. Responsibilities include defining product requirements, evaluating AI outputs, improving quality, synthesizing customer feedback, prioritizing roadmaps, and shaping product culture.