Top Machine Learning Jobs in Louisville, KY

The Senior Machine Learning Engineer will lead AI initiatives, develop ML infrastructure, establish data engineering best practices, and collaborate across teams to enhance healthcare technology services.

As a Machine Learning Engineer, you will fine-tune models, shape data pipelines, evaluate AI behavior, and collaborate on product features in a high-autonomy environment.

The role involves fine-tuning machine learning models, designing datasets and pipelines, and ensuring product quality and safety for a new AI application.

Develop and optimize machine learning models for financial and operational workflows at Netflix, ensuring model reliability and integration with studio applications.

The role focuses on enhancing detection frameworks using machine learning to identify malicious activities and minimize risks for Netflix.

Build and deploy ML systems that detect fraud and automate security decisions, while collaborating with cross-functional teams.

As a Senior AI/ML Software Engineer, you'll develop AI systems for finance, collaborating on ML tools, models, and deployment to enhance user experience and efficiency.

The role involves developing and optimizing intelligent agents using large language models, collaborating with the team, and solving technical problems.

The role involves building and maintaining ML pipelines, optimizing workflows, and contributing to product strategy with a focus on usability.

The ML Platform Engineer will develop and scale ML infrastructure, automate workflows, and collaborate with data scientists to deploy models efficiently in production.

Design and deploy machine learning models for personalized recommendations and search on Zillow's platforms. Collaborate with cross-functional teams to enhance user experience.

As an Associate Technical Architect in Machine Learning, you will design and develop advanced ML models on AWS, ensuring scalability and reliability while collaborating with cross-functional teams.

The Machine Learning Engineer develops AI solutions for cancer care using expertise in ML algorithms and genomic data, collaborating across teams.

The role involves developing ML algorithms for autonomous driving, including training models, evaluating performance, and improving behavioral models.

The Principal Machine Learning Engineer leads the design and implementation of advanced ML systems to enhance cybersecurity capabilities, collaborating with Data Scientists and Engineers.

As an MLOps/ML Platform Engineer, you will build and manage ML systems, optimize workloads, and ensure production model reliability while collaborating across teams.

As a Machine Learning Engineer at Zillow, you will develop and implement machine learning models, prototypes, and algorithms, collaborating closely with scientists and engineers. You will focus on deploying applications, improving reliability, and fostering innovation in AI solutions.

Design and implement deep learning models for 3D computer vision, develop ML pipelines, deploy and monitor models on cloud platforms, and document findings.

The role involves designing and implementing user-friendly interfaces, collaborating with data scientists on ML model deployment, and maintaining CI/CD pipelines for ML workflows.

Lead the development of credit risk models, collaborating with consultants and technology teams, and implement LLM-based agents for dynamic decision-making.

Join a team focusing on end-to-end ML Ops for the insurance sector. Develop and deploy ML solutions, build infrastructure, and solve business challenges using advanced technologies.

The Senior ML Engineer designs and develops advanced machine learning models, collaborates with teams, monitors model performance, and implements MLOps practices for scalability.

The Senior Machine Learning Engineer will build and operate ML systems, manage the model lifecycle, and mentor team members while ensuring sustainability data accuracy.

The Lead Data/ML Engineer will design and maintain scalable data pipelines and AI systems, ensuring data reliability and collaboration with product teams.

The role involves designing and implementing data and AI architectures, developing data pipelines, and integrating machine learning solutions while fostering Agile methodologies and collaboration.