Top Senior Machine Learning Jobs in Milwaukee, WI

The Machine Learning Engineer will develop AI products by designing and deploying ML models, optimizing pipelines, and collaborating with teams.

The Senior ML Engineer will design evaluations for AI features, optimize pipelines, and ensure quality in ML systems while collaborating with cross-functional teams.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

As a Senior Data Scientist, you will develop models to extract insights from complex datasets, focusing on temporal and geospatial features, while collaborating with engineering teams to implement solutions.

Collaborate to scale self-driving systems, build training frameworks, profile model performance, and evaluate emerging technologies for training and inference.

Lead the design and deployment of scalable ML infrastructure, focusing on MLOps and LLM strategies, while mentoring team members and ensuring operational maturity.

Lead ML Performance Optimization for autonomous driving, collaborating across teams, implementing optimization techniques, and mentoring engineers for career growth.

As a Senior Machine Learning Engineer, you will build and productionize ML models, develop scalable infrastructure, and mentor teams to optimize marketing products.

As a Senior Machine Learning Engineer, you will design and deploy object detection models, collaborate with teams, and enhance ML solutions.

The role involves designing and implementing cloud-native infrastructure for AI/ML workloads, optimizing Kubernetes environments, and contributing to open-source MLOps tooling.

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

The Machine Learning Scientist will design and evaluate algorithms for media processing, collaborate with cross-functional teams, and expand expertise in computer vision and related fields.

The Staff Software Engineer will architect, implement, and maintain foundational ML infrastructure and feature stores for Reddit, collaborating across teams to advance ML capabilities.

The role involves designing, developing, and deploying ML models, collaborating with cross-functional teams, and improving model performance through testing and experimentation.

Lead the development of ML algorithms for robotic manipulation, focusing on multimodal perception and real-world deployment, integrating with other robotics functionalities.

The Senior Machine Learning Research Engineer will develop and deploy deep learning pipelines, optimize model training, and collaborate with scientists to enhance AI/ML capabilities for cancer detection.

Lead architectural vision and development of scalable infrastructure for self-driving technology, mentoring engineers and overseeing complex projects.

Develop and optimize deep learning models for trajectory generation in autonomous vehicles, focusing on planning, control, and real-time inference.

Design and build ML infrastructure components for autonomous vehicles, ensuring scalability and robustness for high-volume data processing and model training.

The Senior Solution Innovation Architect will design and implement AI/ML solutions on the Snowflake platform, collaborate with customers, and provide technical expertise in ML and AI applications.

The role involves developing advanced multimodal customer experiences using AI, mentoring others, and refining AI processes for Zillow's platforms.

The Senior Power System Studies Engineer designs and applies AI/ML techniques for power system optimization, conducts simulations, and mentors junior engineers.

The position involves driving AI/ML product development for personalized experiences, partnering across teams, and launching impactful products.

The Senior Machine Learning Consultant designs and develops machine learning solutions while mentoring team members and collaborating with clients. Responsibilities include conducting R&D on AI/ML models, optimizing model performance, and ensuring adherence to ethical AI practices.

The role involves building ML infrastructure, creating data pipelines, ensuring data quality, and collaborating with data scientists to optimize models.