Top Machine Learning Jobs in Provo, UT

Design and operate large-scale, AI-native cloud infrastructure (especially Kubernetes/AKS). Improve service quality, automate incident prevention/remediation, accelerate engineering productivity, and integrate AI tools into development workflows.

Conduct research on AI tokenomics by evaluating model architecture trends, building simulation models for training and inference efficiency across hardware and workloads, diligencing companies using model tokens, and forecasting economic impacts for investors, corporates, and policymakers.

The Product Marketing Manager will develop go-to-market strategies, create compelling messaging, perform market research, and collaborate with product and sales teams to position Oscilar's AI risk platform effectively.

Identify business challenges and translate them into AI initiatives; architect AI solutions using appropriate models, frameworks, and infrastructure; guide data science and engineering teams through proof-of-concept development and deployment; mitigate bias and model drift through monitoring; and communicate an AI vision aligned with business goals.

Reviews and refines AI-generated content and data outputs, develops prompts, evaluates model performance using rubrics, conducts independent research and fact-checking, annotates data, and summarizes complex findings in technical reports. Works asynchronously with project leads and domain experts to improve AI output quality and analytical standards.

Lead strategy and roadmap for Brain Health & Detection, drive AI/ML-powered detection and anomaly systems, partner with engineering and data science, set success metrics, and lead end-to-end product execution and adoption for scalable service health intelligence.

Develop and optimize scalable, low-latency bot threat detection, request risk detection, and fraud prevention products. Responsibilities include implementing features, improving existing functionality, designing architectures, testing and deploying code, troubleshooting complex customer issues with Level 3 Support, and analyzing web and mobile platform data. The role requires performant web API development, knowledge of HTTP and common data formats, and integration of machine learning tools and LLMs.

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.

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

Oversee global analytics and algorithm design initiatives for a nonprofit: identify high-impact projects, coordinate with student directors, collect feedback, design and run training for developers and technical advisors, and form partnerships to support implementation. Volunteer commitment ~5-6 hours/week.

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.

Analyze microbiome and longitudinal clinical data, develop biomarkers and microbiome metrics using statistical and machine learning methods, and create visualizations, reports, protocols, and study reports. The role supports research, product development, scientific publications, proposals, and clinical studies while collaborating independently with microbiome experts in a remote-first startup environment.

Adjudicate automated vessel detections humans cant resolve: identify dark/spoofed/low-confidence contacts, investigate AIS/GNSS manipulation and ownership, produce sourced identification records, and supply labeled ground truth to improve detection models.

Manage the development and implementation of Evio Compass, an analytic product identifying patient risks, while guiding cross-functional teams to drive customer success and enhance ML/AI product features.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

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.

Design, build, and deploy production-grade ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM applications, and scalable data pipelines with observability and MLOps practices for cloud and on-prem environments.

Design, build, and deploy production ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM features, data pipelines, observability, MLOps, and containerized deployments across cloud and on-prem environments.

Lead hands-on analytics work to build data products, AI-first applications, and production analytics on Snowflake and Azure. Partner with Data Engineering and business stakeholders to identify high-value monetization, efficiency, and growth opportunities, deliver end-to-end solutions, and scale the function by hiring and mentoring a team while ensuring data governance and compliance.

Leads data science strategy across Mexico and Brazil, manages and mentors a distributed team, and remains hands-on building and deploying machine learning models. Establishes modeling standards, infrastructure, delivery practices, and technical roadmaps while partnering with credit leadership on underwriting, valuation, impact measurement, and P&L analysis. Requires strong applied machine learning expertise, prior data science leadership, business communication skills, and understanding of credit or underwriting.

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.

Lead the strategy and roadmap for Demandbase’s orchestration platform, including workflow builders, triggers, actions, integrations, and AI-assisted automation. Partner with engineering to scale high-volume, low-latency event processing and support emerging agentic use cases. Drive platform extensibility, reliability, transparency, and user efficiency across enterprise GTM workflows.

Develop and optimize machine learning and statistical models for fraud detection and anti-money laundering. Analyze large datasets to identify fraudulent patterns, build scalable data pipelines and features, evaluate model performance, and collaborate with engineering, product, and operations teams. Communicate insights to technical and non-technical stakeholders while maintaining data privacy and security compliance. The role offers significant ownership in building Oscilar’s early machine learning stack within a remote-first startup.

Own the technical architecture, strategy, and roadmap for an autonomous construction robotics stack spanning localization, planning, controls, and safeguarding. Make build-versus-reuse-versus-buy decisions, design safety systems, guide integration and field validation, establish shared technical foundations across autonomy programs, and mentor engineers. The role requires architecting and shipping production autonomous systems, strong compiled-language software skills, broad systems judgment, and 10+ years of relevant experience.

The Senior Machine Learning Researcher will design experiments, research new algorithms, and collaborate on deploying models for computer vision and robotics applications.