Top Machine Learning Engineer Jobs in Chicago, IL

As a Senior AI/ML Engineer at CTC, you will shape AI strategy, evaluate technologies, build AI capabilities, and enhance workflows for engineering and trading teams.

The Machine Learning Engineer designs, builds, deploys, and maintains machine learning models, optimizing their performance for business value. Responsibilities include managing ML pipelines and collaborating with data teams to implement MLOps best practices.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

This role involves developing ML tools and frameworks, supporting data science environments, and leading projects from design to execution. Candidates need strong programming skills and a quantitative background.

The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.

Develop, validate, and deploy machine learning models and scalable ML pipelines. Preprocess and analyze data, run experiments, collaborate with senior engineers and stakeholders, and support model risk governance and regulatory-compliant AI applications (fraud detection, credit scoring, marketing analytics).

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

Design, build, and operationalize production-grade AI/Machine Learning solutions and MLOps services. Deploy models and API services to AWS and GCP using CI/CD and IaC, implement workflow automation, monitor post-production performance, research generative/ML techniques, and mentor junior engineers while collaborating with cross-functional data, cloud, and architecture teams.

Design, build, and operationalize production-grade ML and generative AI solutions and MLOps services. Collaborate with data, product, cloud, and architecture teams to deploy and monitor models in AWS and GCP. Implement CI/CD, IaC, workflow automation, and API services to ensure scalable, repeatable model deployments and observability.

The role involves developing and improving TTS/Voice Generation models, training, fine-tuning, evaluating speech models, and collaborating across research, engineering, and product teams in a fast-paced startup environment.

As a Machine Learning Engineer, you will design, build, and deploy ML models for underwriting at Stripe Capital, ensuring performance while collaborating with multiple teams.

As a Forward Deployed Machine Learning Engineer, you'll build and deploy machine learning models, enhance system performance, and collaborate with Data Science and Engineering teams for effective solutions.

The role involves building and optimizing a machine learning and simulation platform, supporting MLOps, model deployment, and infrastructure modernization, while mentoring engineers.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

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

Design, develop, and deploy production ML models and scalable pipelines. Collaborate with cross-functional teams, optimize model performance, implement MLOps deployments, monitor model health, and document experiments and metrics.

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 Principal Machine Learning Engineer will fine-tune and optimize LLMs for various applications, develop AI products, and enhance ML infrastructure in collaboration with cross-functional teams.

As a Machine Learning Engineer, you will design and build AI capabilities, develop scalable ML infrastructure, and collaborate on production systems in the real estate domain.

The Junior-Midlevel Developer will build and enhance Dumroo.ai's AI-powered education platform, collaborating on software components, data pipelines, and machine learning features.

The Lead AI/ML Engineer evaluates emerging technologies, leads teams in adopting solutions, and provides technical leadership while mentoring junior specialists.

Own Coinflow's ML layer: explore transaction and behavioral data, build production models and decisioning systems, establish ML/data practices, define core metrics, and partner with Engineering, Product, and Operations to embed intelligence into products and tooling.

Lead design, build, and production deployment of ML and GenAI solutions (LLMs, RAG, multi-agent systems, recommender and RL models). Architect scalable, secure inference and MLOps pipelines, mentor MLEs, collaborate with stakeholders to define roadmaps, and measure model performance and business impact. Implement fine-tuning, retrieval, orchestration, and monitoring for enterprise-grade AI products.

The Machine Learning Engineer will develop ML models, maintain data pipelines using Databricks, and collaborate with Data Scientists to productionize models while ensuring data quality and reliability.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.