Top Remote Machine Learning Jobs in Provo, UT

Lead product strategy and execution for data and AI platforms, driving GenAI/LLM initiatives, cross-functional collaboration, responsible AI governance, experimentation (A/B testing), measurement of model impact, and mentoring product teams to embed scalable ML capabilities into clinical and member experiences.

Own pre-sales technical engagement: consult customers, deliver technical presentations and demos (web, iOS, Android), lead POCs, support RFP/RFI responses, manage onboarding and integrations, and advise sales, product, and engineering teams on implementation and value realization.

Design, build, and scale backend systems and APIs for high-transaction consumer products. Collaborate with product, credit, compliance, support, and analytics teams. Contribute to code reviews, technical planning, security, and operational excellence. Mentor peers and promote engineering best practices.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

Design, implement, and scale ML-based solutions for search and advertising; define data collection, evaluation, and production serving strategies; analyze data to inform development; communicate cross-functionally; produce technical reports; and stay current with advances in LLMs, vision models, and generative AI.

Leads the end-to-end execution layer for machine learning, including data pipelines, large-model training and fine-tuning, evaluation, inference, deployment, monitoring, and reliability. Designs scalable GPU-based systems, optimizes performance and cost, partners with research and application engineering, and translates model capabilities into measurable production improvements. Also provides technical leadership, judgment, and support for high-impact ML delivery.

Lead end-to-end development of an AI-driven decision-support system for multi-sensor data. Responsibilities include building data ingestion and fusion pipelines, training and deploying supervised and unsupervised ML models, optimizing near-real-time inference, creating GPU-accelerated dashboards, integrating modular containerized systems, and supporting secure deployment and testing. The role works directly with the founder, owns technical delivery autonomously, and collaborates with subcontractors on human factors, model validation, and security auditing.

Industry Expert who reviews and defends advanced AI/ML and systems engineering projects, chairs architecture and executive review panels, hosts occasional technical sessions, and sets standards for instructors. The role requires production-scale engineering experience, live architecture critique, a public technical footprint, strong English, and expertise in agentic systems, LLM evaluation, model serving, cloud infrastructure, distributed systems, observability, RAG, and enterprise deployments.

Build and deploy LLM-powered agents, workflows, and production integrations using platform templates, pipelines, and guardrails. Develop and run evaluation suites, integrate business systems and data sources, instrument cost and quality telemetry, and collaborate with business users to iterate within bounded scopes. The role requires strong Python and TypeScript, API development, prompt and context engineering, and production experience with agents, RAG, and tool use.

Build and deploy LLM-powered agents and workflows using templates, pipelines, and guardrails. Develop comprehensive evaluations, integrate AI solutions with business systems and data sources, and instrument applications for cost and quality telemetry. Collaborate with business users to iterate within defined scopes. The role requires strong Python and TypeScript skills, production experience with LLM applications, API development, prompt and context engineering, retrieval, and healthcare data handling.

Build and deploy AI-powered applications for customers, combining Python and TypeScript application engineering with LLMs, generative AI, agent orchestration, APIs, distributed systems, and cloud platforms. Partner with stakeholders to understand requirements, design scalable architectures, rapidly prototype solutions, integrate AI capabilities, and evolve proofs of concept into production systems. The role also involves customer-facing consulting, technical decision-making, and collaboration throughout the solution lifecycle.

The Enterprise Account Executive will drive revenue by engaging with enterprise insurance clients, managing the sales cycle, and fostering strategic relationships with executives, leveraging Vellum's data analytics platform.

Lead development of new credit line management programs by designing, testing, and scaling policies. Own end-to-end analytical work using SQL/Python, partner with Data Science and Product, and present data-driven recommendations to senior stakeholders to improve spend recovery, utilization, and line-management performance.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions, architect scalable infrastructure, and implement data pipelines across multi-cloud environments while collaborating with cross-functional teams to maximize business value.

Lead the integration of AI and digital solutions in manufacturing processes, driving adoption and measurable impact on efficiency, quality, and performance.

The Staff Machine Learning Engineer will lead AI initiatives, architect LLM systems, design evaluation frameworks, and mentor engineers.

As a Senior Machine Learning Engineer, you will enhance diffusion models, conduct research, collaborate on system implementations, and communicate findings effectively.

As a Principal Solutions Architect, you will oversee technical architecture for VA IT modernization, writing prototypes, guiding engineering teams, and representing Credence to VA stakeholders. You will also contribute to capture strategy and mentor engineers on compliance and integration.

The Principal Product Manager - Growth will lead growth initiatives, focusing on user engagement, retention, and the use of AI to enhance product strategies and experiences.

Design, build, and deploy machine learning systems for controlling quantum processors. Develop reinforcement learning and Bayesian methods for QEC calibration, and work cross-functionally with product and R&D teams.

The Senior Technical Architect will lead AI SDLC transformations, create architectural solutions, mentor teams, and drive innovation in regulated industries.

As a Regional Sales Director, you'll lead a sales team, develop business plans, and drive sales growth by managing complex cycles and nurturing talent.

Provide on-call MLOps support for machine learning teams by triaging pipeline issues, debugging workflows, identifying root causes, and maintaining reliable model development operations. Collaborate with senior engineers to improve tooling, documentation, and processes, while communicating technical findings across teams. The role requires Python, foundational PyTorch and model pipeline experience, plus familiarity with CI/CD, monitoring, logging, and orchestration tools.

Own the full lifecycle of clinical text extraction models, from problem framing and annotation strategy through production deployment, evaluation, monitoring, and retraining. Build clinical NLP pipelines, establish defensible quality and error-analysis systems, and apply LLMs using rigorous evaluation, observability, and cost controls. Partner with clinical data and backend engineering teams while addressing PHI protection, de-identification, auditability, and access controls. As the first ML hire, set technical direction and potentially build and lead the future ML team.

Lead end-to-end product strategy and delivery for a core marketplace area, collaborating with engineering, UX, and design. Conduct qualitative and quantitative research, run agile sprints, measure results with analytics, and pioneer AI/ML product features and workflows to improve user experience and platform impact.