Top Remote Machine Learning Engineer Jobs in Chicago, IL

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.

The Staff Machine Learning Engineer will define and build ML capabilities, design production systems, and lead ML strategy in a high-growth AI cybersecurity company.

Lead the development of advanced perception algorithms for self-driving vehicles. Collaborate and mentor engineers, optimize algorithms, and implement sensor fusion for robust perception systems.

Develop ML/RL models and infrastructure for AV simulations, optimize training loops, and support project timelines in autonomous vehicle tech.

As a Machine Learning Engineer at Twilio, you will architect and maintain data pipelines, build ML training workflows, and collaborate with cross-functional teams to deliver compliant, resilient services, ensuring quality and performance.

The role involves developing AI technologies for customer support at Airbnb, leveraging ML systems to enhance customer experience through innovative solutions.

As a Software Engineer II, you'll develop backend systems, support ML platform features, collaborate across teams, and ensure system availability.

The Senior AI/ML Engineer will architect multi-agent workflows, build evaluation frameworks, and mentor teams, focusing on integrating advanced AI with global risk data.

The Staff Machine Learning Engineer will lead AI initiatives, architect LLM systems, design evaluation frameworks, and mentor engineers.

The Machine Learning Engineer will design, build, and maintain scalable ML systems, optimize ML pipelines, implement MLOps, and collaborate with teams to deploy models into real-time products.

As a Senior AI Engineer, you will develop and optimize Generative AI applications, manage AI pipelines, collaborate with clients, and ensure production delivery with MLOps best practices.

Build and maintain MLOps pipelines, deploy and monitor ML models as scalable services, transform and integrate healthcare data (FHIR/HL7), ensure reproducible feature management, and uphold HIPAA/HITRUST security for production ML in clinical systems.

As a Machine Learning Engineer, you'll design and build ML models, manage the ML lifecycle, collaborate with teams, and mentor peers based on experience level.

The role involves developing, adapting, and implementing machine learning algorithms for computer vision tasks in power grid analysis. Responsibilities include experimentation, error analysis, and project ownership.

In this role, you will design and develop AI and machine learning models, maintain data pipelines, evaluate model performance, and collaborate with cross-functional teams to integrate AI capabilities into web-based applications.

As a Staff Machine Learning Engineer at Twilio, you will build and maintain data pipelines and ML infrastructure, ensuring high-quality data and model performance while collaborating with product and security teams.

As a Staff Machine Learning Engineer, you will develop, productionize, and deploy ML models for clinical use, ensuring real-world effectiveness through hands-on coding and infrastructure building.

As a Machine Learning Engineer, you'll design and implement detection systems, enhance model efficacy, and analyze datasets to improve email detection against security threats.

The Machine Learning Engineer will develop editable visuals combining computer vision and machine learning, enabling chat-driven figure editing and leveraging biological understanding to produce accurate visuals.

Develop and deploy end-to-end machine learning solutions, collaborate with cross-functional teams, and implement MLOps frameworks while monitoring model performance in production.

The Machine Learning Engineer will design, develop, and deploy ML models using Google Cloud tools, focusing on Document AI and Vertex AI, ensuring scalable applications and efficient performance.

As a Machine Learning Engineer in Computer Vision, you'll develop AI solutions using advanced algorithms, focusing on image classification, segmentation, and video processing tools.

The ML Engineer will leverage deep learning for natural language processing tasks, impacting Entefy's products while requiring strong machine learning fundamentals and NLP expertise.

Lead architecture and engineering for production-grade ML in healthcare: design MLOps CI/CD, scalable low-latency inference for LLMs and classical models, build reliable data pipelines for FHIR/HL7/DICOM, manage cloud IaC and observability, ensure HIPAA/HITRUST compliance, and mentor engineering teams to operationalize agentic AI workflows.

The ML Engineer will contribute to the automated discovery engine, developing RL frameworks, synthetic data engines, and evaluating performance using proprietary datasets.