Top Machine Learning Jobs in Chicago, IL

Lead internal AI training and solution development across Grainger's corporate and business functions, advising leaders on AI integration and impact. Design prototypes and drive functionality while collaborating with technical teams.

Lead design, development, and production deployment of AI/ML solutions and conversational chatbot platforms. Own end-to-end implementation, MLOps/CI-CD, containerized deployments, solution architecture, security and governance, mentor engineers, and collaborate with product, enterprise architecture, and vendors to deliver scalable, monitored AI systems.

The Senior/Staff Data Scientist will build and deploy predictive models for consumer decisioning and business optimization, focusing on machine learning and statistical modeling. Responsibilities include model development lifecycle, data exploration, collaboration with teams, and improving product outcomes.

The Solution Architect will lead AI transformation engagements, providing expertise in AI strategy and architecture, focusing on customer success, governance, and enabling organizational change.

Responsible for validating payment network models, including fraud and AML. Engage with stakeholders, improve model accuracy, and leverage innovative technology for data analysis.

The Senior Associate, Data Scientist will partner with cross-functional teams to identify risks associated with models and validate machine learning models across the enterprise, enhancing decision-making while ensuring model governance and risk management.

This internship focuses on researching low-latency ML inference and hardware acceleration, involving project ownership, collaboration with engineers, and presenting findings.

The AI Engineer Manager leads the Data and Analytics Engineering team in developing AI solutions, manages client accounts, analyzes data, and fosters team leadership and relationships with clients.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

Lead and coach a data science team to design, develop, and deploy predictive and prescriptive analytics. Partner with business leaders to identify opportunities, drive adoption of models and insights, manage vendors, and establish data science methodology to deliver measurable business impact.

As a Senior AI Engineer, you'll design and implement AI-driven solutions, focusing on full-stack development and production-grade applications while mentoring junior team members.

In this role, you will drive revenue by promoting Braze AI tools, perform proofs-of-concept, and lead educational programs while collaborating with various stakeholders.

Lead teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.

Lead Data Scientist partners with business leaders to identify opportunities, design, develop, and deploy advanced analytics and ML solutions. Responsibilities include data preparation, modeling, feature engineering, delivering insights and visualizations, establishing standards, and directing associate data scientists, contractors, and consultants to produce measurable business value.

The role involves designing, building, and deploying computer vision models for vehicle damage detection, covering the entire ML lifecycle and collaborating across teams.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

The Engineering Manager, Data Science will lead a team to drive machine learning initiatives in AdTech, focusing on optimization and modeling strategies to enhance client success and operational efficiency.

The Director, AI Solutions Architect leads the development of scalable AI solutions, ensuring quality and compliance while collaborating with cross-functional teams.

Lead the design and implementation of critical Safety AI initiatives, focusing on real-time perception systems for edge devices and optimizing models for production deployment in safety-critical environments.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

Lead end-to-end AI strategy and delivery for clients: translate executive goals into investor-grade business cases, design production-ready LLM/agent/RAG solutions, partner with engineering to deploy measurable AI products, mentor consultants, and build reusable IP to scale engagements.

Lead design, development, and productionization of ML and LLM/NLP systems. Own feature engineering, model evaluation, monitoring, and bias analysis. Partner with Product and Engineering to drive operational impact and act as senior technical owner and reviewer for data science work.

Lead the development of fraud prediction models using machine learning, collaborating across teams to build, scale, and monitor models in production.

Lead a team of ML engineers to develop fraud detection models, defining strategies, driving model evolution, and ensuring effective integration with cross-functional teams.

The role involves deploying and supporting CrowdStrike's AI capabilities in cybersecurity, optimizing threat detection, and mentoring teams on AI solutions.