Top Senior Machine Learning Jobs in Louisville, KY

The Director of Product Management for the Data Platform will drive the adoption and operational effectiveness of AlixPartners' data initiatives, ensuring stakeholder engagement and compliance.

Lead the design and development of ML models for autonomous agricultural robots, overseeing the full ML lifecycle and collaborating with cross-functional teams.

The Global Strategic Feasibility Analytics Lead develops feasibility data analytics initiatives, transforms data into insights, collaborates with stakeholders, and drives data-driven decision-making for study planning.

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.

The Senior Machine Learning Engineer will design and implement high-performance CTR and CVR prediction models, refine systems for user behavior modeling, and ensure model reliability through performance monitoring while engaging with stakeholders.

The Staff AI/ML Engineer will design and build AI-powered services, develop machine learning models, and optimize workflows, collaborating across teams to deliver quality solutions.

The Principal Machine Learning Engineer will lead the development of AI/ML solutions to enhance user personalization within Yahoo Mail, mentor teams, and drive innovation while maintaining code quality and engineering standards.

The role involves designing, building, and managing data pipelines and machine learning solutions for veterinary care, utilizing cloud services and various programming languages while collaborating within an Agile team.

The Staff Machine Learning Engineer at Niche will lead ML initiatives, build and deploy models, measure results, mentor staff, and drive business growth through data-driven solutions.

The Senior Machine Learning Engineer will personalize user experiences, build systems for model training, collaborate with cross-functional teams, and contribute to product strategy.

The engineer will build end-to-end applications, analyze data trends, deploy solutions, and improve process efficiency for the solar industry.

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.

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.

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

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.

Lead the development and implementation of ML/AI solutions for AML and Financial Crime, collaborating with teams to optimize workflows and ensure compliance.

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.

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.