Top Machine Learning Jobs in Peoria, IL

Lead the Generative AI engineering team in building and executing AI strategies, managing platform lifecycle, and collaborating with stakeholders for impactful AI solutions.

The Principal AI/ML Platform Engineer leads the development and delivery of ML and GenAI platforms, ensuring scalability, compliance, and performance across various workflows and products, while mentoring the engineering team.

Lead a team of ML engineers to deliver AI/ML solutions on AWS, focusing on practice strategy, operational excellence, and building partnerships.

As a Machine Learning Engineer, you will design, develop, and deploy machine learning systems, collaborate on AI features, and ensure reliable production performance.

The Senior Product Manager will develop AI tools, collaborating with research, engineering, and design to meet user needs and drive business value.

As a Cloud Machine Learning Engineer at Hugging Face, you will build ML solutions leveraging cloud technologies, integrate models, design APIs, and contribute to documentation and community advocacy.

As a Senior Staff Machine Learning Engineer, drive AI safety initiatives, design monitoring systems, and collaborate cross-functionally to ensure robust, safe AI usage in community support products.

Lead the design and execution of ML-based targeting products, improving advertiser outcomes while mentoring junior engineers and collaborating with cross-functional partners.

The role leads predictive modeling and machine learning initiatives, mentors team members, and drives innovations in data science for credit risk and operations.

The Principal Machine Learning Engineer will lead ML lifecycle projects, developing AI strategies, and implementing advanced machine learning solutions for government clients, while ensuring data integrity and operational efficiency.

The Senior Software Engineer will design and build infrastructure for ML model training and deployment, focusing on AWS technologies, reliability, and collaboration with ML teams.

As an ML Engineer, you will design and manage ML pipelines, collaborate on privacy engineering, and implement MLOps practices, ensuring robust and scalable infrastructure.

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

The Principal Machine Learning Engineer will improve diffusion models, conduct research, implement techniques, and collaborate on production-ready systems in AI for fashion.

The Data Scientist will develop machine learning models to optimize software build processes, analyzing large datasets and collaborating with teams for improvements.

The Staff Software Engineer, AI/ML will design and develop intelligent agents, integrate them with existing systems, optimize performance, and collaborate with product teams, focusing on innovative AI technologies.

The engineer will develop and evaluate machine learning models for ultrasound devices, lead small teams, curate datasets, and document performance results.

Lead the deployment and optimization of AI models for inference and agentic platforms, focusing on lifecycle management and collaboration with infrastructure teams.

Lead the architecture and development of ML systems, integrating various models and tools, ensuring they are secure and efficient while mentoring engineers.

The Senior Machine Learning Engineer at SmarterDx will deploy, maintain, and optimize machine learning models, collaborating across disciplines to integrate these solutions and improve clinical AI outcomes.

Build and implement AI solutions for cybersecurity, focusing on vulnerability detection and exploitation. Collaborate with senior engineers and mentor junior team members.

The role involves leading ML/AI solutions, managing technical roadmaps, collaborating with stakeholders, and driving innovation in products and services.

The Software Engineer will develop machine learning infrastructure, optimize models, and create tools for data analysis while collaborating with a diverse team.

The Machine Learning Solutions Architect designs and implements data solutions, overseeing model deployment and ensuring robust performance and integration within customer environments.

Design and architect AI/ML solutions, build document parsers and classifiers, maintain AI systems, and collaborate with cross-functional teams.