Top Remote Machine Learning Jobs in Minneapolis, MN

Design, develop, and deliver machine learning models for clinical data. Collaborate with stakeholders and optimize production ML systems.

Lead development of a greenfield data product by partnering with customers and product teams to build analytics and models (simulation, Bayesian networks, optimization, ML). Maintain existing analytics, improve predictive churn models, and translate customer needs into production-grade SQL/dbt pipelines, dashboards, and data-driven product features.

Lead AI/ML projects focusing on health applications, design and scale AI systems, and collaborate across teams to improve solutions using advanced machine learning methodologies.

As a Senior Machine Learning Engineer, you'll design and manage ML infrastructure, work with Data Science to implement models, and oversee system health and reliability.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

The Technical Marketing Manager will oversee marketing for AppSec, AI/ML Security, and Research & Engineering, focusing on content creation, social media, demand generation, and analytics. This role requires technical fluency and collaboration with engineering teams to effectively communicate complex concepts to technical and business audiences.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

As a Systems Architect, you'll define and drive the infrastructure architecture for AI/ML workloads, design multi-cloud strategies, manage compute orchestration and storage systems, and lead capacity planning, while also collaborating with engineering leadership.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

Design, implement, and optimize scaled lifecycle campaigns across email and in-product channels to drive activation, revenue, retention, and cross-sell. Use marketing automation, behavioral data, and ML techniques to personalize experiences, analyze performance, and collaborate across growth, product, sales, and data teams.

The role involves researching, developing, and implementing AI solutions, optimizing models, integrating AI into workflows, and collaborating with teams to enhance business efficiency.

Drive measurement, causal inference, and experimentation to optimize content promotion and personalization. Build robust metrics, partner with product and engineering, surface discovery opportunities, and independently deliver high-impact analytics and ML solutions.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

The AI/Machine Learning Specialist designs and implements AI solutions, collaborates with cross-functional teams, and continuously improves ML processes.

Lead design and delivery of generative AI features end-to-end, prototype and productionize early-stage AI systems, set technical direction, mentor engineers, and collaborate with product and design to drive measurable product impact.

Design and implement credit strategies using data, machine learning, A/B testing and advanced analytics to optimize underwriting, pricing, and credit line decisions. Lead end-to-end analytics for credit card products, monitor portfolio performance, conduct root-cause analysis, partner cross-functionally, and communicate findings to stakeholders.

Lead the Performance ML squad, managing and mentoring engineers while driving the development, deployment, and strategy of predictive models for advertising.

As a Sr. Machine Learning Engineer, you'll develop ML solutions for healthcare, manage data pipelines, write production-ready software, and own ML services end-to-end.

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

The Senior Data Engineer will develop real-time streaming data pipelines for pricing algorithms and machine learning models, ensuring low-latency data delivery and system reliability. Responsibilities include collaborating with other teams, defining architectural standards, and mentoring junior engineers.

The Group Product Manager will lead the Real Time Decisioning and 3D Secure authentication product suites, focusing on fraud management and security while enhancing customer experiences. Responsibilities include strategy development, cross-functional collaboration, and product optimization.

The VP of Engineering will lead a high-performing team to develop AI-enabled technologies, managing technical vision and execution strategies while ensuring product reliability and security in complex environments.

Lead pre-sales technical engagements for Conversational and Generative AI solutions, collaborate across teams, and design value-driven demos for enterprise customers.