Top Senior Machine Learning Jobs in Salt Lake City, UT

Lead design, execution, and interpretation of A/B tests and quasi-experiments; apply causal inference methods; partner with product, engineering, and marketing; mentor data scientists; build experimentation frameworks; extract and analyze data using SQL and Python; communicate results to stakeholders.

Lead integration of state-of-the-art AI/ML into Netflixs content platform and publishing tools. Build roadmaps, incubate ML systems from idea to production, partner with researchers and engineers, automate promotional asset creation, optimize distribution and localization, and measure impact with data-driven evaluation.

Design and deliver secure, high-performance microservices and APIs. Develop backend services in Java and Python, integrate ML components, build front-end service layers, deploy containerized applications to cloud platforms, and collaborate in Agile teams to ensure scalable, test-driven solutions.

The Cloud Inference Engineer is responsible for building and maintaining a scalable LLM inference platform, focusing on distributed systems and machine learning technologies while collaborating across teams to optimize performance.

Lead product strategy and execution for a B2B SaaS marketing analytics platform. Translate research into requirements, own the backlog, partner with engineering and GTM, define success metrics, and ship API- and data-heavy features for technical users.

The Senior Product Manager will set product direction, own the development lifecycle, collaborate with teams, and ensure high-quality outputs. This role requires strong opinions on product quality and customer insights.

The Director of Computer Vision will lead technical vision, research, and execution in developing scalable AI-driven computer vision solutions, managing teams, and enhancing performance metrics.

Lead the Decision Science function, designing ML models, overseeing experimentation frameworks, and ensuring model adoption across the company, driving operational and commercial improvements.

Own strategy and execution to expand Pagaya's auto asset class: drive end-to-end enterprise sales to OEMs, banks, and dealers; close complex deals; build C-level relationships; coordinate across Risk, Tech, Product, Legal, and Data; monitor market trends; and evangelize Pagaya externally.

Lead and build a team that drafts and submits state-specific rating rules, underwriting guidelines, and forms; manage filing execution via SERFF, handle objection responses, coordinate cross-functional stakeholders, establish operating rhythms, improve documentation and controls, and coach staff to scale filing expertise and regulatory execution.

Lead net-new enterprise sales into Fortune 500 and large mid-market accounts building AI/ML systems. Prospect and create outbound pipeline, run long consultative sales cycles, orchestrate pilots and phased rollouts, influence technical and executive stakeholders, and partner with solution architects to close complex, high-value deals.

Author and verify rigorous multiple-choice computer science assessment items across many CS domains to create gold-standard benchmarks for AI research. Produce correct answers, nine plausible distractors, solution explanations, difficulty labels, and authoritative references. Review and edit questions for technical accuracy, clarity, and reproducibility. Contribute asynchronously as an independent contractor, ~10+ hours/week, fully remote.

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.

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.

Lead and deliver complex, cross-team AI product programs, drive agent-first SDLC adoption, ensure integration and operational readiness of AI workflows, define metrics, communicate risks and status, and standardize TPM best practices across Product and Engineering.

Lead sales operations for seller acquisition at a marketplace: design pipeline and lead flows, remove onboarding friction, build SOT dashboards and forecasts, track listing health and KPIs, design incentive and quota programs, own CRM and sales enablement, and implement AI-driven automation and predictive analytics to scale seller and listing growth.

Partner with a retained search firm to place software engineers and quant developers at top hedge funds. Provide candidate flow from your network; firm supplies clients, process, and fees. Remote, commission-only role with placement and pipeline incentives. Apply with placement examples, outreach metrics, and a candidate submission.

Lead and align ML, data, and engineering teams to define multi-year AI roadmaps, deliver production ML solutions, ensure robust data pipelines, set success metrics tied to business outcomes, and grow/mentor senior managers and engineers.

Lead and build a data science organization to create a prediction engine for vendor matching, order routing, and supply chain optimization. Anchor projects to P&L, design measurement and experiment frameworks, ship rapid wins, hire and coach data scientists, work hands-on in modeling and technical design, partner with product and engineering (Snowflake), and evolve systems toward agentic AI while reporting impact in dollar terms.

Build, ship, and own end-to-end ML models for vendor matching, order routing, and supply-chain optimization. Partner with data engineering to productionize models, quantify impact, document work, and implement decision logic components toward agentic AI in a fast-moving healthcare startup environment.

Own end-to-end modeling for vendor matching, order routing, and supply-chain optimization. Build predictive, causal, RL and OR solutions; design autonomous decision logic; quantify counterfactual impact; ship production models with data engineering; mentor senior data scientists; write technical design docs; partner on quarterly priorities and expand into revenue cycle and finance domains.

Lead and execute product strategy for Everyday Money: define product thesis and roadmap, ship product lines, run AI innovation lab for agentic consumer experiences, manage and develop PMs, partner with design, Credit, and external partners, and own business economics and compliance for durable retention and monetization.

The Staff Product Manager will define product strategy, lead the product lifecycle, collaborate across teams, and drive innovation in claims processing software.

Lead procurement strategy and supplier selection for inbound products and services. Manage RFIs/RFPs, negotiate contracts with Legal, administer Coupa purchase orders, reconcile invoices, and apply AI/ML and reporting tools to optimize procurement processes while collaborating with cross-functional senior stakeholders.

Lead and deliver complex, cross-team AI platform programs: manage schedules, risks, integration of AI workflows and agents, enable operational readiness, drive TPM best practices, and communicate status and metrics to stakeholders in a remote, multi-timezone environment.