Top Machine Learning Engineer Jobs in Chicago, IL

Lead the technical direction of DeepWalk's computer vision platform, enhancing ML systems and data pipelines for sidewalk inspection.

The Senior Machine Learning Operations Engineer is responsible for designing, building, and maintaining scalable ML systems and infrastructure while mentoring junior engineers and leading project initiatives.

As an AI/ML Software Engineering Intern, you'll develop AI-driven features, collaborate in Agile teams, and gain hands-on software engineering experience.

The Senior AI/ML Engineer at Cooley will design, build, and maintain enterprise-scale AI/ML solutions across cloud platforms, optimize performance, and collaborate on AI implementations.

As a Senior Machine Learning Engineer, you'll design and develop workflows utilizing vision-language models, manage data pipelines, and collaborate with multiple teams to enhance model accuracy and efficiency.

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

The Senior Data Engineer will develop real-time streaming data pipelines for pricing algorithms and machine learning models, ensuring low-latency data delivery and system reliability. Responsibilities include collaborating with other teams, defining architectural standards, and mentoring junior engineers.

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.

As a Staff Software Engineer, you will lead the development of computer vision systems for sidewalk inspection, overseeing model lifecycle, system architecture, and mentoring while improving deployment practices.

The Senior Machine Learning Platform Engineer will build foundational components for ML models, mentor junior engineers, and optimize streaming pipelines. Responsibilities include enhancing ML infrastructure and ensuring data quality.

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

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.

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, optimizing, and deploying machine learning models for edge environments, focusing on computer vision. The engineer will collaborate with teams to integrate models and improve inference efficiency while mentoring peers and upholding company values.

As a Machine Learning Engineer, you'll develop and deploy ML models for medical imaging, collaborate with teams, and optimize for production environments.

Lead the end-to-end machine learning lifecycle for AI products, managing data pipelines and model development to optimize performance and accuracy in production.

The Principal Machine Learning Engineer will develop multimodal technologies, mentor engineers, and drive product innovation in agentic AI systems.

Responsible for building and evolving ML/AI applications on AWS, integrating machine learning solutions, and managing automated pipelines for deployment and performance monitoring.

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

Develop and optimize machine learning models for fraud detection. Collaborate on model deployment and conduct experiments, ensuring data quality and driving innovation in digital trust.

The Full Stack Developer will implement OpenAI and GPT-3 tools to develop processes for creating content and editing media for podcasts.

As an AI & Machine Learning Engineer, you will develop and deploy intelligent systems for robotic control, including machine learning models for vision, predictive analytics, and optimization within real-time production environments.

The AI/ML Engineer develops models for skills inference and verification, creates recommendation systems, and integrates AI into Cengage's platforms to enhance career outcomes.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.