Top Remote Machine Learning Jobs in Salt Lake City, UT

The job involves building responsive web dashboards, advanced data visualizations, and analytics tools for unmanned aircraft systems, requiring a deep understanding of UI/UX design and data presentation.

Design, build, and deploy machine learning models for a payments platform, overseeing end-to-end solutions and experimentation, while monitoring models in production.

The Machine Learning Engineer will develop AI/ML solutions on AWS, optimize data pipelines, and support cloud migration projects while collaborating with stakeholders.

Manage AI/ML projects from Proof of Concept to Minimum Viable Product using Agile methodologies while ensuring stakeholder communication and project alignment.

Design, build, and operate production-grade ML systems for personalization, search, and recommendations. Own end-to-end pipelines from data ingestion and modeling to deployment, monitoring, and iteration, ensuring scalable, reliable, and observable services.

Design and maintain datasets, build and evaluate domain-specific ML and vision-language models for real-time privileged access threat detection; deploy and optimize Python/Docker inference services integrated with WebSocket/WebRTC and protocol-level interfaces; monitor and document production models.

The Staff ML/AI Platform Engineer will design, prototype and deploy AI/ML models, optimize pipelines, mentor junior engineers, and collaborate closely with other teams to develop machine learning solutions.

The Director of AI & ML is responsible for establishing and leading the AI function, defining AI strategy, building a high-performing team, and delivering production-grade ML and AI solutions within healthcare payer workflows.

Responsible for designing, building, and operating AI-powered features, scalable APIs, and maintaining integrations within ClickHouse's AI/ML ecosystem.

Seeking a Principal AI/ML Researcher and Engineer to lead research and development in Bayesian Learning and Reinforcement Learning. This role involves architecting large-scale AI systems, model development, and driving technical strategy for innovative AI platforms that enhance personalization and decision-making at Airbnb.

Responsible for fine-tuning state-of-the-art LLMs, optimizing models for deployment, and driving AI architectural decisions. Collaborate with cross-functional teams to develop impactful AI products.

The Senior ML Engineer will develop and optimize machine learning solutions for audience intelligence, build production pipelines, and collaborate with cross-functional teams to enhance user engagement and revenue.

As a Staff Machine Learning Research Scientist, you will lead ML research, develop evaluation frameworks, mentor researchers, and collaborate on clinical AI solutions.

The role involves designing and building AI components for a platform, specifically focusing on NLP and ML for catalog mapping and anomaly detection, along with feedback mechanisms.

The role involves developing and deploying machine learning solutions, optimizing models, and collaborating with cross-functional teams. Responsibilities include cloud architecture, algorithm engineering, and infrastructure best practices.

The Applied Scientist AI/ML Intern will work on building data pipelines, finetuning LLMs, and deploying AI models in a collaborative team environment.

Lead a team of machine learning data scientists, overseeing model development for fraud detection and risk assessment, and ensuring quality throughout the model lifecycle while mentoring the team.

As an MLOps/ML Platform Engineer, you will build and manage ML systems, optimize workloads, and ensure production model reliability while collaborating across teams.

As a Senior Machine Learning Engineer, you will develop and deploy ML models for health data analysis, collaborating with cross-functional teams to ensure reliability and regulatory compliance.

Design and implement ML infrastructure for scalable deployment, collaborate across teams, optimize ML systems, and enhance tooling.

As an Applied Machine Learning Platform Engineer, you'll design and maintain training infrastructure, manage distributed pipelines, and optimize data workflows for machine learning models.

As a Senior Machine Learning Engineer, you'll design and develop infrastructure and models for AI-powered applications while collaborating with teams to enhance product functionality.

The VP of Research, Machine Learning will set research direction for AI systems, focusing on context representation, reasoning, and evaluation frameworks while ensuring product safety and alignment.

Responsible for building and maintaining end-to-end ML pipelines and deploying production-grade ML systems. Tasks include model fine-tuning, evaluation, and collaboration with engineering teams.

Lead computer vision projects and develop ML models for power grid analysis while mentoring engineers and ensuring software quality standards.