Top Remote Machine Learning Jobs in Chicago, IL

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.

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.

Lead the SDL and Cash Line ML teams, developing innovative machine learning models to improve lending solutions and expand credit access. Collaborate with cross-functional teams to drive product strategy and enhance model performance, while mentoring a team of ML scientists.

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.

As a Principal Applied Scientist, you'll define the technical vision for offer optimization and conversion modeling systems, ensuring alignment across teams while overseeing large technical initiatives and contributing to real-world machine learning solutions.

Manage a team of ML engineers to build and optimize Affirm's economic decisioning engine using advanced ML techniques. Collaborate across teams, provide technical leadership, and mentor engineers while driving a cohesive long-term ML strategy.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

As an Applied Machine Learning Engineer, you will develop AI and ML models to improve healthcare outcomes. Collaborate with teams to implement and optimize machine learning techniques and algorithms.

Design and build machine learning systems for Coinbase, responsibly use generative AI tools and copilots, apply human-in-the-loop practices, and deliver measurable efficiency, cost, and quality improvements while collaborating in a remote-first environment with periodic in-person surges.

Lead ML feature strategy and engineering for fraud detection, owning end-to-end pipelines, validating features at scale, and translating analytics into production ML systems. Drive tooling and architecture decisions, mentor junior team members, partner cross-functionally with product and risk teams, and apply practitioner-level ML knowledge to detect and prevent account takeover and scam activity.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

The role involves designing and deploying strategies for congestion revenue rights, applying quantitative methods, and developing machine learning models.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

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

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

As a Principal Machine Learning Engineer, you will develop multimodal AI experiences, design agent interactions, and lead cross-team initiatives while ensuring AI safety and reliability.

Design, develop, and implement AI/ML models; analyze large datasets; integrate AI solutions into existing systems; apply MavLink for autonomous systems; collaborate across teams and improve ML development processes.

Lead architecture and development of a SaaS platform for data center energy procurement. Build forecasting, contracting, and monitoring modules; implement AI tools on AWS (Bedrock, SageMaker); hire and mentor engineers; translate business logic into scalable systems; deliver demos to investors and customers.

The role involves leading a team of Forward-Deployed Machine Learning Engineers to deliver AI solutions, manage project execution, and enhance operational excellence.

Lead the creation and optimization of machine learning algorithms, develop and refine production-grade models, and drive testing of innovative algorithms using historical data.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

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

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

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