Top Senior Machine Learning Jobs in Milwaukee, WI

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 Machine Learning Engineer will execute the full ML lifecycle, collaborating on model implementation and improving customer experiences through data-driven insights.

Design and implement ML infrastructure for scalable deployment, collaborate across teams, optimize ML systems, and enhance tooling.

As a Senior Machine Learning Scientist, you will design, build, and optimize deep learning models for biological data analysis, ensuring high-quality outputs and leading complex projects from conception through deployment.

Lead the end-to-end machine learning lifecycle for AI products, managing data pipelines and model development to optimize performance and accuracy in production.

The Senior Machine Learning Engineer will manage the full ML lifecycle, collaborating with teams to develop scalable systems that improve product decisions and empower monetization strategies.

The Principal Machine Learning Engineer will develop multimodal technologies, mentor engineers, and drive product innovation in agentic AI systems.

As a Full Stack Engineer, you'll develop production-ready AI and ML features, build APIs, design scalable systems, and implement frontend solutions using Angular.

As an ML Engineer, you will build and productionize predictive models for ad inventory and campaign performance, contributing to the growth of Netflix's ad platform.

Develop and optimize unimodal and multimodal perception models for 3D/BEV terrain and surface inference, build large-scale data pipelines and annotation tools, deploy and optimize models on edge compute, collaborate with robotics/software/hardware teams, mentor juniors, and translate research into production-grade autonomous vehicle perception systems.

Lead design, training, and iteration of diffusion-based generative models producing 3D geological models conditioned on geophysical and borehole data; curate synthetic and real datasets; adapt models for projects and collaborate with teams.

Lead AI and engineering efficiency initiatives, integrating cutting-edge technologies into engineering processes, while promoting innovation and continuous improvement.

Develop and maintain end-to-end ML pipelines on Azure, manage infrastructure as code with Terraform, and optimize deployment processes in collaboration with data and product teams.

The role involves applying AI/ML techniques to develop model systems for healthcare, collaborating across teams, and conducting R&D.

Lead computer vision projects and develop ML models for power grid analysis while mentoring engineers and ensuring software quality standards.

As a Senior Machine Learning Engineer, you will design ML infrastructure, build AI features, and collaborate with cross-functional teams while managing large data sets.

Develop, evaluate, and deploy AI systems and machine learning models, focusing on NLP and multimodal models. Collaborate with teams and publish research.

This role involves deploying and optimizing machine learning models for autonomous vehicle motion planning, ensuring performance and reliability in production settings.

Lead a team to develop large-scale data analysis frameworks and ML models for autonomous vehicles, driving project execution and innovation.

As a Senior Machine Learning Engineer, you'll develop and optimize ML systems, implement pipelines, and collaborate with cross-functional teams to enhance Yahoo's data capabilities.

The role involves delivering advanced analytics and machine learning solutions, collaborating with stakeholders, and mentoring junior data scientists.

The Senior Machine Learning Operations Engineer will build and operationalize the ML Ops platform to deploy and monitor machine learning models, focusing on infrastructure, automation, and integrating ML workloads within the AWS-native architecture.

Lead technical direction for AI across products, architect RAG services, mentor engineers, and ensure compliance in AI usage.

As a Staff Machine Learning Engineer, you will design and evaluate ML models, optimize performance, and work with stakeholders to deliver AI solutions.