Top Senior Machine Learning Jobs in Chicago, IL

Lead end-to-end deployments of AI for hotel revenue teams: integrate PMS/CRS/RMS, ship ML/optimization models and agentic workflows, validate recommendations with revenue managers, define metrics, drive adoption, and hire/mentor the forward deployed engineering team.

Senior individual contributor responsible for leading pet/P&C insurance pricing model development (GLMs and ML), owning end-to-end projects, performing EDA and root-cause analysis, communicating results to stakeholders, and mentoring junior team members.

The Senior Manager for Machine Learning will lead the ML team, coordinate initiatives, and enhance product development in a collaborative environment.

Conduct research and develop identity and probabilistic-matching models for Netflix's ad-supported tier. Apply ML and statistical methods, ensure privacy-preserving solutions (differential privacy, anonymization), prototype and deploy production models, deliver datasets and tools, and partner with product, engineering, and business stakeholders to measure and drive impact.

The Staff Machine Learning Engineer will lead ML systems development for personalization and ranking, design architectures, and mentor team members, ensuring reliable operations at scale.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

Lead machine learning initiatives, oversee product development, improve execution pace, enhance team reliability, and foster team growth at Hightouch.

Act as the technical lead in enterprise sales: run technical discovery, design and deliver customized demos and POCs, assess API/cloud/model fit, address technical objections, support contract negotiations, and relay product feedback to engineering while staying current on AI/ML trends.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

Lead design and production deployment of ML models focused on pricing, availability, forecasting, and optimization. Build data infrastructure, governance, testing/monitoring, and dashboards. Partner with executives and cross-functional teams, mentor others, and establish scalable data-science practices and experimentation frameworks.

Lead development and deployment of cutting-edge ML models for pricing, design and analyze experiments, collaborate with product and engineering, present findings to stakeholders, and lead technical projects to influence team output and business metrics.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

Customer-facing technical role partnering with regional AEs/SEs to architect, prototype, and deploy AI/ML solutions on Snowflake. Build MVPs/PoCs, enable regional teams, deliver demos/workshops, synthesize customer feedback for product teams, and travel to support strategic US Major accounts.

Lead and oversee enterprise ML and statistical modeling efforts, build and mentor data science teams, ensure model governance and compliance, collaborate cross-functionally to deliver scalable AI solutions that drive business outcomes, and advance research and adoption of cutting-edge ML methods.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

As a Senior Machine Learning Engineer, you will enhance diffusion models, conduct research, collaborate on system implementations, and communicate findings effectively.

Design, build, and deploy machine learning systems for controlling quantum processors. Develop reinforcement learning and Bayesian methods for QEC calibration, and work cross-functionally with product and R&D teams.

Develop and scale machine learning training systems for robotics data, optimize training pipelines, and collaborate with ML researchers to enhance autonomy models.

Embed with clients to gather requirements and design AI-driven solutions for fraud and fincrime. Architect, train, evaluate, and deploy custom AI agents and workflows, optimize model performance, establish risk metrics and evaluation pipelines, and collaborate with engineering/product teams to scale into production.

Lead end-to-end research applying advanced ML/DL (transformers, GNNs, RL, ensembles) to generate alpha across digital asset markets, build production-grade pipelines, prevent leakage/overfitting, analyze microstructure and on-chain data, and mentor junior researchers.

As Director of AI/ML, lead the ML organization, set technical vision, mentor a high-performing team, and contribute to model development and production deployment.

Conduct ML research for query understanding, ranking, clustering, and AI-powered search. Prototype and productionize algorithms, define data and evaluation requirements, design scalable systems, collaborate with engineers, run experiments, and publish patents/papers to integrate state-of-the-art ML into Yahoo Search products.

Design, build, and deploy scalable AI and machine learning solutions, leading full AI lifecycle, collaborating with teams, and ensuring systems align with client needs.

Design and deploy machine learning models for financial document processing, optimize large language models, collaborate with cross-functional teams, and guide junior peers in a fast-paced environment.