Top Remote Machine Learning Jobs in Milwaukee, WI

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

The ML Ops Engineer will fine-tune AI models, manage model inference, and ensure high performance across infrastructures while collaborating with engineering teams to implement solutions.

The Sr. Machine Learning Engineer will build tooling and services for ML and generative AI solutions, focusing on deployment, evaluation metrics, and cross-functional collaboration.

The Senior Software Engineer will own large-scale data mining workflows, improve ML products through high-quality datasets, and analyze model performance across driving scenarios.

Lead AI and machine learning projects, create workflows and models, analyze data from diverse sources, and present insights to non-technical audiences.

The AI & Machine Learning Director will lead machine learning projects, design data workflows, and utilize advanced data analysis and visualization to drive business insights.

As an AI/ML Data Engineer, you will design and build data and ML infrastructure to create personalized student experiences, working on ETL processes, feature stores, and collaborating with product and data science teams.

Lead development of a large-scale machine learning platform, optimizing model training, data processing, and collaborating on MLOps, while ensuring scalability and performance.

Lead development of data pipelines and workflows for ML models, design scalable data processing environments, and ensure high data quality.

As a Machine Learning Engineer, you will develop online prediction systems and offline recommendation engines to optimize e-commerce profitability by leveraging machine learning models and data-driven insights.

The Senior Full Stack Engineer will develop AI/ML features for ClickHouse Cloud, integrating AI capabilities and building user-friendly interfaces.

As a Senior Python Engineer at ClickHouse, you will enhance the Python ecosystem for data scientists and ML teams, ensuring efficient data integration and optimizing workflows within the open-source environment.

As a Senior Machine Learning Engineer, you'll design and build AI systems, manage ML lifecycles, and create recommendation and retrieval systems while collaborating cross-functionally.

Design and build infrastructure for ML model training and deployment. Collaborate with teams and monitor performance using AWS tools. Focus on reliability and efficiency in high-availability environments.

The Solutions Engineer will drive the adoption of AI-powered solutions in the electric utility sector, providing technical consulting and customer enablement. Responsibilities include gathering requirements, architecting solutions, leading RFI/RFP processes, and delivering training. Extensive travel is required for client engagement.

The role involves developing machine learning models for Netflix's Studio, collaborating with teams, and scaling ML solutions for data analytics.

As an AI/ML Ops Engineer, you will architect and operate ML pipelines, automate CI/CD processes, and collaborate with cross-functional teams to enhance engineering productivity.

The role involves designing scalable AI solutions, managing large-scale AI deployments, building client relationships, and delivering presentations. Requires experience in MLOps and knowledge of ML ecosystems.

The Machine Learning Engineer will enhance search retrieval, train ranking models, build query understanding systems, and ensure robust pipelines for Reddit's AI-driven products.

As a ML Engineer focused on inference, you'll design and optimize deep learning models for real-time communication AI applications, collaborating with cross-functional teams and ensuring production readiness.

As a Research Intern, you will work on AI/ML projects, contributing to the development of the Nebula LLM and applying machine learning techniques to real-world problems.

Design and maintain scalable machine learning infrastructure, collaborating with data scientists, ensuring performance, security, and compliance of AI systems.

The ML Engineering Intern will contribute to the Nebula LLM development, tackle machine learning challenges, and gain hands-on experience in AI and language technology.

As a Software Engineer, you'll enhance the user experience of ML tools, optimize workflows, and collaborate with product managers on ML infrastructure projects.

As a Machine Learning Engineer, you will develop and deploy AI/ML solutions, collaborate with product managers and engineers, and improve learning experiences.