Top Machine Learning Jobs in Salt Lake City, UT

Set the technical vision for data science, lead complex statistical and machine learning model development from concept through production, and architect scalable modeling platforms and pipelines. Develop credit risk, pricing, and loss forecasting models; establish model governance standards; partner with senior leaders; mentor data scientists; and communicate technical strategy to executives. The role emphasizes production deployment, monitoring, cloud architecture, and high-impact decision-making across the business.

Develop and maintain production machine learning models, build scalable training and serving technologies, optimize real-time and batch ML pipelines, and monitor model performance and drift. The role involves deep neural networks, recommendation systems, automated retraining, ML research, engineering excellence, and communicating technical concepts to diverse audiences. Candidates need 6+ years of industry ML experience, strong coding skills, and experience deploying neural networks at scale.

Develop and execute enterprise AI and machine learning product strategies, roadmaps, governance, and platform capabilities. Partner with engineering, design, data, and business teams to identify opportunities, prioritize investments, define success metrics, and deliver measurable outcomes. Lead discovery, AI adoption, vendor evaluation, and executive communication while enabling organization-wide AI capabilities and operational excellence.

Lead technical client onboarding, migrations, solution design, integrations, data orchestration, troubleshooting, and project delivery for Movable Ink’s AI-powered personalization platform. Partner with clients and internal teams to implement custom workflows, APIs, webhooks, and data solutions. Conduct training and workshops, provide product expertise, advise on roadmap improvements, and support long-term client success across email and mobile marketing programs.

Product Counsel will advise product, engineering, data science, marketing, compliance, and sales teams throughout the product lifecycle. Responsibilities include counseling on regulatory compliance, privacy, intellectual property, consumer protection, AI and machine learning, data rights, platform architecture, APIs, identity and account security, and marketing. The role translates legal requirements into technical guidance, supports AI governance, monitors evolving laws, and develops scalable legal processes for a fast-paced technology company.

Develop statistical analyses, experiments, predictive models, and machine learning solutions for Sales and B2B Marketing. Analyze large transaction-level datasets, evaluate business performance and product features, deliver stakeholder reporting and recommendations, and take data science projects from development through production. The role requires strong SQL, Python or R, advanced modeling expertise, and familiarity with consumer finance, sales operations, and B2B marketing.

Lead enterprise data security architecture to protect sensitive data across its lifecycle. Define strategies for encryption, key management, tokenization, masking, DLP, classification, database security, and Zero Trust. Advise execs and engineering on secure design patterns for data platforms (e.g., Starburst), cloud/on-prem systems, APIs, data pipelines, and AI/ML workloads. Develop roadmaps, evaluate technologies, mentor staff, and drive secure-by-design adoption across the organization.

Design, build, and support high-throughput, low-latency LLM inference and data pipelines; collaborate with data scientists to post-train and evaluate models; implement scalable, production-ready systems with strong testing, monitoring, and performance focus; mentor engineers and iterate on architecture, reliability, and user-facing AI applications.

Manage analytics and performance insights for Brokerage Client Services. Collaborate with stakeholders, data teams, and technology teams on business performance monitoring, compensation, big data use cases, reporting, and ad hoc analytics. Prepare, visualize, govern, and analyze data using low-code tools, present concise data stories, and translate insights into actions that improve associate, leader, and customer experiences.

Analyze large datasets to uncover actionable insights for Brokerage Client Services. Support data quality, governance, management, visualization, preparation, and diagnostic reporting while building trust in data products. Collaborate across multiple projects, present findings to stakeholders, identify anomalies, document processes, and evaluate tools and approaches that improve associate, leader, and customer experiences.

Lead the strategy, roadmap, launch, adoption, and ongoing improvement of an AI-powered clinical data insights platform. Partner with Data Science, Engineering, and application teams to create reusable capabilities, define platform metrics, prioritize investments, evaluate build-versus-buy decisions, and align senior stakeholders across clinical, technical, and business objectives.

Leads long-range workforce and resource planning for contact center operations. Owns demand forecasting, staffing, capacity, headcount, cross-skill, and scenario models across business lines and channels. Develops advanced predictive and prescriptive analytics, performance metrics, and decision-support tools using complex data sets. Advises executives on resource allocation, service levels, costs, and business performance while governing data quality and analytical processes. Leads capacity planning analysts and drives continuous improvement through automation, machine learning, and improved forecasting methodologies.

Lead GitLab’s company-wide strategy for autonomous, agentic software development workflows. Identify and validate AI opportunities across the SDLC, build prototypes and reference architectures, establish evaluation frameworks and safety controls, and drive internal adoption. Partner across Engineering, Product, Infrastructure, Security, Architecture, and Data and ML teams to scale reliable, observable, compliant agentic capabilities into customer-facing products. Mentor senior technical leaders and represent GitLab externally on AI-assisted development and productivity measurement.

Leads high-visibility product programs focused on market adoption, analyst relations, customer advisory boards, executive briefings, and industry events. Translates technical product roadmaps into compelling market value propositions, synthesizes analyst and customer feedback, and provides actionable insights to product leadership. Partners cross-functionally with Product, Marketing, and executive stakeholders while supporting strategic initiatives and external-facing communications.

Supports payer modernization and health services consulting engagements by analyzing operational challenges, optimizing processes, applying business analytics, engaging stakeholders, implementing quality standards, and guiding transformation initiatives. Develops operational support frameworks, conducts market research, manages change, and advises clients on improving service delivery and business performance while mentoring junior team members.

Build and operate production machine learning systems for Safety AI, including low-latency APIs, data pipelines, model serving, evaluation, monitoring, and rollout infrastructure. Process large-scale camera and telematics data, optimize cloud and edge-to-cloud execution, track model performance and drift, and partner with applied scientists, firmware engineers, platform teams, and product managers to deliver reliable safety features.

Own the strategy, architecture, development, deployment, monitoring, and continuous improvement of production personalization and recommendation systems. Build custom embeddings, ranking models, and shared representations across feeds, search, and recommendations. Lead ambiguous problems from concept to measurable customer impact, establish AI evaluation standards, partner with product and data teams, make cross-team technical decisions, and coach senior engineers.

Engineer AI-powered threat detections, automated response playbooks, and continuous adversary emulation. Apply machine learning and LLMs to security operations, conduct threat hunting and AI red teaming, map coverage to MITRE ATT&CK, and develop detection-as-code through CI/CD. Build production-grade Python integrations, measurable containment capabilities, and safe autonomous defenses with guardrails. Mentor security professionals and collaborate across threat response, cyber defense engineering, and platform teams.

Design, build, and operate high-throughput, low-latency ad-serving infrastructure processing millions of requests per second. Optimize GPU-powered TensorRT inference, feature stores, model serving, benchmarking, experimentation tooling, and system reliability. Partner with machine learning engineers to productionize models and own systems through design, deployment, observability, capacity planning, incident response, and optimization.

Leads large-scale enterprise application development, modernization, and sustainment programs. Oversees Agile teams, program governance, schedules, budgets, risks, resources, stakeholder communications, cloud modernization, DevSecOps, AI, user adoption, and cybersecurity compliance. The role coordinates technical and business stakeholders, manages Appian and Google Cloud initiatives, drives continuous improvement, and ensures delivery quality, security, performance, and alignment with government objectives.

Lead product-focused data science and machine learning initiatives, including exploratory analysis, production model development, evaluation frameworks, generative AI, graph-based machine learning, recommendation systems, and personalization. Collaborate with engineering, product, and business teams to deliver high-impact solutions, influence strategy, and communicate insights to technical and non-technical stakeholders. The hybrid role requires four days per week in the Greater Boston area.

Staff Backend Engineer responsible for building data and machine learning systems that provide competitive travel-market intelligence. The role involves setting technical strategy, designing APIs and backend architecture, prototyping solutions, partnering with product and ML engineers, conducting design and code reviews, driving engineering best practices, and mentoring junior engineers.

Freelance writers summarize recent machine learning research papers for The Batch, an AI newsletter reaching over two million professionals and students. Writers must understand machine learning technology, explain complex research clearly in an established format, and communicate effectively in English. The role is intended for graduate students and postdocs in machine learning, with negotiable freelance compensation.

Provides remote customer support for a SaaS product through email, messaging, Zoom calls, and screenshares. Resolves common product and configuration issues, documents and escalates complex problems, educates customers, and maintains communication through resolution. Contributes to help-center content, internal documentation, and support process improvements while identifying recurring issues and communicating customer needs to Product, Engineering, and Customer Success teams.

The Corporate Controller will lead accounting operations, month-end close, financial reporting, audits, tax compliance, payment reconciliations, internal controls, treasury, and exit-readiness activities. The role manages accounting systems, automation initiatives, vendor relationships, and accounting team development while partnering with FP&A, Payments, HR, and senior leadership. The position requires strong U.S. GAAP expertise, including ASC 606, audit leadership, AP operations experience, and familiarity with SaaS, payments, or FinTech environments.