Top Remote Machine Learning Jobs in Salt Lake City, UT

Leads LaunchDarkly’s global partnerships and alliances strategy across GSIs, SIs, cloud, VAR, and technology partners. Builds the partnerships organization, partner programs, co-sell motions, services offerings, and PRM ecosystem. Owns partner-sourced pipeline, influenced revenue, budgets, forecasting, executive relationships, enablement, and cross-functional collaboration across Sales, Product, Services, Marketing, Finance, Legal, and Customer Success.

Leads enterprise AI-focused sales campaigns across a regional territory, advising C-suite and technical AI buyers on data platform and infrastructure solutions. Partners with account executives, solution architects, engineers, product teams, GSIs, and channel partners to develop use cases, reference architectures, ROI frameworks, and joint go-to-market strategies. Owns pipeline discipline, forecasting, account planning, complex deal orchestration, and AI solution positioning for enterprise workloads.

Design, build, and integrate AI-enabled applications using C#/.NET and Azure. Develop data ingestion, transformation, and automation pipelines for structured and unstructured data. Implement and optimize LLM/Generative AI solutions, build APIs, and support end-to-end delivery from design through production handoff while partnering with business stakeholders.

Build and maintain scalable, highly available payments risk systems that detect, mitigate, and resolve fraud and other malicious activity. Develop service-oriented APIs, real-time risk services, vendor and payment-network integrations, monitoring, and alerting. Collaborate with product managers, data scientists, operations, and engineering teams to evolve risk strategies, deliver product features, conduct experimentation, and maintain high engineering standards.

Lead the assessment, roadmap, requirements, and implementation of fraud and dispute products across card, ACH, instant payments, account takeover, transaction monitoring, and risk decisioning. Partner with customers, financial institutions, vendors, engineering, sales, marketing, and support teams. Evaluate emerging technologies, build business cases, support go-to-market efforts, conduct UAT, and serve as the fraud product subject matter expert.

Develop and deploy deep learning models for AI-guided antibody drug discovery and target identification. Design experiments, build systems biology models, and create in silico and in vitro validation approaches. Collaborate with biological and wet-lab teams, present findings, publish high-impact research, and mentor scientists and engineers.

Leads engineering managers and software teams building customer-facing front-end applications and internal and external APIs. Sets technical direction, oversees delivery, manages risks and dependencies, improves engineering quality and security, develops talent, supports hiring, and partners with product and design. The role drives innovation and scalable software solutions for connected vehicle and fleet operations.

Leads the engineering strategy, architecture, development, operations, and continuous improvement of an enterprise agentic AI foundation. Establishes scalable engineering standards, operating models, governance, and reusable platform services that enable AI products and intelligent workflows. Partners with product, data, infrastructure, security, and business teams to modernize existing systems, guide cross-functional delivery, monitor operations, and communicate priorities, risks, and investment needs to senior leaders. Manages and develops product or engineering leaders while driving measurable business value.

Leads the strategy, architecture, and execution of an enterprise data platform supporting analytics, machine learning, operational systems, and AI applications. Manages and mentors data platform engineers while remaining hands-on with architecture, reliability, technical direction, and troubleshooting. Oversees pipelines, orchestration, governance, security, observability, data contracts, migrations, and platform operations. Partners cross-functionally to translate business needs into scalable technical solutions and communicates decisions to technical and non-technical stakeholders.

Analyze microbiome and longitudinal clinical datasets, develop microbiome metrics and biomarkers using statistics and machine learning, create visualizations and reports, draft clinical research documents, support product and study development, and contribute to scientific publications and proposals.

Generate and qualify inbound and outbound leads through high-volume phone, email, and social outreach. Schedule introductory meetings and demos, maintain accurate CRM records, and collaborate with marketing on lead-nurturing strategies. The role requires strong communication, resilience, time management, and interest in building a SaaS sales career. This is a fully remote position open to candidates anywhere in the United States.

Lead data science for Root's digital partnerships channel, managing a team to drive growth, profitability, experimentation, forecasting, optimization, and measurement. Partner with cross-functional teams to improve acquisition economics, influence product and technical roadmaps, deliver executive reporting, and establish scalable operating processes.

The Customer Success Engineer will lead deployments, serve as a technical advisor, and support customer engagement, focusing on product enhancements and user experience.

Research, draft, edit, and validate practitioner-facing US federal tax articles using AI tools. Ensure accuracy and currency, collaborate with data scientists, and align content with tax firm workflows and customer needs while helping build the content function.

OneSix is seeking motivated professionals for future opportunities in data and AI consultancy. Interested candidates should submit their resumes to stay in touch.

The Senior Director leads research in Application Platforms & AI, guiding clients in AI strategy and market trends, while producing critical research content and engaging with clients directly.

The Senior Machine Learning Engineer will develop core ML models, manage data pipelines, and collaborate with stakeholders to deliver scalable ML solutions.

Join Invoca's Talent Community to stay updated on job openings and to explore exciting career opportunities across various departments.

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

Lead vision, strategy, and roadmap for Fetch's referral growth engine. Own end-to-end referral lifecycle, build incentives, experimentation, AI-driven personalization, and cross-functional initiatives to drive MAU growth and durable network effects.

Lead product strategy and roadmap for a unified data platform, spanning ingestion, modeling, and an intelligence layer. Partner with engineering and data science to deliver cloud-native pipelines, curated analytic models, and ML productization. Drive governance, metrics, cross-functional alignment, backlog management, and Agile practices to maximize platform value for internal teams and clients.

Manage a portfolio of SaaS customers, build relationships, monitor usage, prevent churn, handle support and troubleshooting, identify upsell/renewal opportunities, and relay customer feedback to product and engineering.