Top Remote Machine Learning Jobs in Milwaukee, WI

As a Senior/Staff ML Systems Engineer at Quilter, you'll design and maintain ML infrastructure for automated PCB component placement, manage data pipelines, and lead systems design reviews while ensuring project efficiency and reliability within a fully distributed team.

The Senior Machine Learning Operations Engineer will design, build, and maintain ML infrastructure, streamline model deployment, and monitor performance to ensure the success of machine learning models at The Athletic.

The Lead AI/ML Engineer evaluates emerging technologies, leads teams in adopting solutions, and provides technical leadership while mentoring junior specialists.

As a Senior Machine Learning Engineer, develop LLM evaluation frameworks and agentic AI workflows to extract insights from conversations and optimize customer experiences.

Build and operate high-throughput experimentation and recommendation infrastructure. Design APIs and services, use agentic AI workflows (LLMs) for development, ensure performance and reliability, participate in on-call, mentor teammates, and codify AI-native engineering practices.

Lead development of cutting-edge LLM and Agentic AI systems for Airbnb customer support, from research and prototyping to production deployment. Collaborate with product, design, and engineering to build scalable ML infrastructure, improve model performance, and implement evaluation, fine-tuning, and guardrails for chat and voice assistants.

As a Machine Learning Engineer in Computer Vision, you'll develop AI solutions using advanced algorithms, focusing on image classification, segmentation, and video processing tools.

The role involves owning and delivering AI-powered features for Calendly, collaborating with multiple teams, and applying machine learning solutions for product enhancement.

The role involves managing the ML lifecycle, developing scalable ML systems, and collaborating on AI-first product solutions focusing on Large Quantitative Models.

Lead design, build, and production deployment of ML and GenAI solutions (LLMs, RAG, multi-agent systems, recommender and RL models). Architect scalable, secure inference and MLOps pipelines, mentor MLEs, collaborate with stakeholders to define roadmaps, and measure model performance and business impact. Implement fine-tuning, retrieval, orchestration, and monitoring for enterprise-grade AI products.

The Senior Manager, Data Science/ML will lead a team to enhance product innovation through data science, focusing on ML and experimentation frameworks that boost customer engagement. Responsibilities include defining product strategy, building ML models, and collaborating with cross-functional teams to shape product roadmaps.

Lead development and maintenance of internal Python SDK frameworks and agentic workflows, build scalable FastAPI-based ML APIs, automate CI/CD with Jenkins and GitLab Runners, use Galileo for model evaluation and observability, and collaborate across teams to deliver production-grade autonomous systems.

The AI & Machine Learning Director will lead client engagements, analyze corporate performance, and drive improvements in profitability through machine learning and data analysis, while also managing business development and team collaboration.

The Senior Vice President will lead projects focused on corporate performance, drive revenue growth, and develop business strategies while utilizing data modeling and machine learning techniques for analysis and solutions.

The Senior Machine Learning Engineer will deploy and maintain ML models, collaborate with cross-functional teams, and optimize ML system performance in a fully remote role.

Design and deploy production recommendation and retrieval engines, build data orchestration pipelines for multiple modalities, implement agentic workflow frameworks, and prototype, optimize, and scale models with monitoring, governance, and low-latency SLAs.

The role involves product management of AI tools, collaborating with research, engineering, and design teams to develop and enhance products, focusing on user needs and market value.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

The role involves improving recommendation systems using machine learning, developing end-to-end ML systems, and collaborating with engineers.

The DevOps Engineer will design, build, and optimize ML and data infrastructure on GCP, mentor a team, and ensure system reliability and performance.

The Lead Machine Learning Engineer will optimize AWS SageMaker, manage ML pipelines, develop infrastructure as code with Terraform, build CI/CD pipelines, and collaborate with data scientists to deploy models in production.

The role involves leading ML strategy, architecting systems, designing algorithms, collaborating with teams, and mentoring engineers in AI for enterprise analytics.

Lead design, development, and production deployment of ML models and GenAI/LLM solutions to optimize clinical trial workflows. Build scalable pipelines, monitoring, and CI/CD for robust production use. Collaborate cross-functionally, mentor junior engineers, and communicate technical results to technical and non-technical stakeholders.

Lead and mentor engineering teams while owning platform architecture (React, Node/Express, Postgres, AWS). Drive TypeScript migration, design ETL and AI/LLM integration frameworks, ensure reliability and observability, manage delivery, incidents, and hiring, and define technical strategy for production ML/AI systems.

As a Senior Software Engineer, you'll build and operate the ML platform, optimizing data operations, managing the feature store, and supporting ML initiatives while driving architectural roadmap decisions.