Top Remote Machine Learning Jobs in Madison, WI

Work on vision-language model development and infrastructure: improve VLM understanding, OCR and function-calling workflows, fine-tuning recipes, evaluation and robustness, and optimize training/serving pipelines. Own end-to-end projects from experiments to production-ready code, collaborating on scale, cost, and reliability.

The Global Process Owner for S&OP leads the design and continuous improvement of the S&OP process, ensures collaboration across functions, and drives digital transformation and automation within the organization.

The VP of Data and AI will define and execute data and AI strategies, lead technical teams, oversee data platform infrastructure, and drive measurable business outcomes.

The Director of System Safety oversees safety functions for autonomous vehicles, managing safety cases, deployment plans, and regulatory relationships while leading a multi-disciplinary safety team.

The Senior Technical Product Manager will lead the roadmap for Aledade's AI Data Platform, collaborating with various teams to enhance AI capabilities and improve healthcare outcomes for patients.

As a Product Manager, you will oversee the inventory management and store ordering solution, conducting user research, collaborating with teams, and driving product vision to reduce food waste.

The Software Engineering Manager will lead a team in creating tools for Cengage Learning Platforms, focusing on AI innovation, team growth, agile delivery, and collaboration.

The Director of Software Engineering will lead teams in creating innovative education tech solutions, strategic planning, and optimizing software delivery processes.

Lead a team of analysts to advance fraud and safety operations through analytics, ensuring robust data products and compliance while empowering stakeholders with actionable insights.

Lead cybersecurity risk assessments, evaluate risks, partner with teams, assess emerging tech security implications, and implement secure solutions.

The CX Outbound Solution Engineer designs and deploys outbound contact center solutions, focusing on operational efficiency and customer engagement. They work with sales to align solutions with customer needs and lead pilot implementations with a strong grasp of outbound regulations and technologies.

Build and ship ML-powered SaaS features end-to-end: design data/feature pipelines, develop and deploy models (forecasting, ranking, recommendations, optimization), define evaluation/A-B testing, monitor drift, integrate models into product workflows, influence roadmap, mentor teammates, and support MLOps and cloud data infrastructure to ensure measurable product impact.

Design and improve ML training frameworks, modularize experiments, adapt fire-hazard detection algorithms for varied electrical environments, build scalable pipelines for high-frequency sensor data, and develop dashboards and tooling to monitor model performance and drift while collaborating across product, data science, and fire safety teams.

Lead and supervise QA team for large-scale Big Data and Whitebox platform testing. Drive test design, automated and manual test strategies, ISTQB compliance, process improvements, project delivery, risk assessment, QA metrics reporting, and cross-functional representation while mentoring engineers.

Develop and deploy production-grade AI/ML models, design end-to-end pipelines, and ensure compliance while collaborating with stakeholders in a federal environment.

As a Machine Learning Engineer, you will design, build, and deploy ML models for underwriting at Stripe Capital, ensuring performance while collaborating with multiple teams.

The Machine Learning Systems Engineer will optimize ML training systems, improve data pipelines, and develop GPU kernels to enhance scalability and performance.

Lead a team of data scientists developing ML-driven products, managing infrastructure, training models, and ensuring production quality while collaborating with senior leadership.

The role involves designing, training, and evaluating ML models, optimizing performance, and collaborating with teams to implement AI technologies in products.

Develop and deploy advanced ML solutions for OCR and NLP, optimizing models for performance and integrating them into production workflows while collaborating with cross-functional teams.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

Lead and grow the AI/ML Engineering team, manage core AI/ML platform development, ensure production-grade service operational excellence, and develop product strategies.

Lead development and execution of MVB's AI and automation strategy, including Generative and Agentic AI and RPA. Partner with business and technical stakeholders to design, pilot, and scale solutions, establish governance and best practices, monitor performance metrics, manage vendors, and deliver training to ensure ethical, secure, and effective AI deployments.

The Sr. Director, Marketing Planning & Transformation will lead integrated marketing strategies and AI execution, optimize marketing operations, and drive team success in a fast-paced environment.

Design, develop, and deploy production ML models and scalable pipelines. Collaborate with cross-functional teams, optimize model performance, implement MLOps deployments, monitor model health, and document experiments and metrics.