Top Remote Machine Learning Jobs in Minneapolis, MN

Lead AI/ML engineering initiatives within a healthcare context, overseeing model development, team mentorship, and strategic integration of AI tools to enhance consumer outcomes.

Lead a team of AI/ML engineers and data scientists to develop GenAI solutions, oversee integration into business workflows, and ensure regulatory compliance.

Manage a team of ML engineers to build and optimize Affirm's economic decisioning engine using advanced ML techniques. Collaborate across teams, provide technical leadership, and mentor engineers while driving a cohesive long-term ML strategy.

The Advisory Agentic Technologist will be the Subject Matter Expert in identity management, driving technical success and strategy, collaborating on agentic AI innovations, and influencing product development, with a focus on the US, Canada, and Latin America.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

As a Staff Applied ML Scientist, you will develop and maintain fraud detection models, conduct research on fraud types, and collaborate across teams to drive product development and real-time decision-making.

As a Senior Applied ML Scientist, you'll develop fraud detection models, research new fraud types, and write production code while collaborating across teams to enhance SentiLink's identity verification solutions.

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.

Design, build, and deploy scalable AI/ML models and pipelines for consumer healthcare. Develop production code (Python/Java/Scala), automate infrastructure (Terraform, Kubernetes), validate model performance, integrate cloud services (Azure/AWS), and collaborate cross-functionally to monitor and document enterprise-scale AI solutions.

Lead and grow an AI/ML engineering team to design, build, and deploy production-grade ML/AI solutions (NLP, NLU, deep learning, CV, ASR). Oversee architecture, MLOps, experiments, model monitoring/versioning, cross-functional collaboration, and ethical AI practices to translate research into scalable business solutions.

Design, build, and deploy production-grade AI/ML models, agentic workflows, and data pipelines using Python, Databricks, LangChain/LangGraph, and Azure. Collaborate with cross-functional teams to translate requirements into scalable LLM applications, implement feature engineering and validation frameworks, and embed responsible AI practices including fairness, security, and monitoring.

Lead product strategy and execution for an AgTech SaaS platform, driving grower workflows, data integration, analytics, IoT partnerships, and commercialization. Own roadmap, write requirements, collaborate with engineering/data science, and measure adoption, revenue retention, and platform usage.

The role involves designing and building scalable data platforms for analytics and AI, optimizing data pipelines, and supporting machine learning workflows. Collaboration with stakeholders to define technical solutions and drive initiatives for data quality and observability is key.

Design, build, and deploy enterprise-scale generative AI and LLM applications, agentic workflows, and RAG pipelines. Develop full-stack solutions using React/Next.js, Python/Node.js, and PostgreSQL; integrate vector databases and optimize retrieval; lead technical design, mentor engineers, and ensure responsible AI deployment and scalability.

As a Senior Machine Learning Engineer, you'll design and develop workflows utilizing vision-language models, manage data pipelines, and collaborate with multiple teams to enhance model accuracy and efficiency.

As a Staff Software Engineer, you will lead the development of computer vision systems for sidewalk inspection, overseeing model lifecycle, system architecture, and mentoring while improving deployment practices.

As a Principal Software Engineer, you'll architect and code backend services and ML models, integrate them with Salesforce, and mentor junior engineers.

Analyze malware and detection data to improve machine learning models, manage false positives, and respond to internal inquiries regarding threat detections.

Develop AI approaches for healthcare, build and test ML models, conduct experiments, analyze data, and collaborate on solutions.

As a Machine Learning Engineer II, you will enhance AI systems for automating customer operations, develop evidence extraction pipelines, and collaborate with teams on model development and deployment.

Lead the machine learning strategy, design scalable ML systems, drive MLOps, mentor engineers, and comply with AI governance.

Independently validate and monitor machine learning models for credit underwriting, credit risk, and fraud detection. Identify model weaknesses, recommend improvements, and collaborate with model owners to remediate findings. Support and maintain the Model Risk Management framework and coordinate with Internal Audit, Internal Controls, and Compliance on audit and regulatory requests.

Lead development and roadmap of AI-powered products for internal teams and advertisers, translating AI concepts into product requirements, partnering with engineering, data science, sales, and ad ops to launch targeting, creative, analytics, and automation solutions.

Research, deploy, and maintain AI models and automation solutions; integrate systems and APIs; manage AWS infrastructure and PostgreSQL databases; build BI dashboards; monitor and optimize AI systems and provide technical support.

The AI Executive Partner will advise C-Suite executives on leveraging AI to drive business outcomes, manage member relationships, and deliver innovative AI solutions.