Top Remote Machine Learning Jobs in Peoria, IL

The Director, Genomics Data will lead genomic data R&D, managing a team to advance data analysis, platform design, and commercialization efforts.

The Enrollment Advisor helps prospective patients through the onboarding process, providing information and support throughout their enrollment in Revero's program.

Lead mobile app attribution strategies, collaborating with teams across engineering and data analytics to optimize performance and feature implementation.

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 role involves leading AI and data science initiatives, overseeing technical execution, fostering team development, and partnering with stakeholders to drive strategy.

The Data Scientist II will enhance marketing strategies through advanced measurement frameworks, statistical models, and cross-functional collaborations to drive revenue growth for Pinterest.

Lead a team of Machine Learning engineers, drive technical direction, oversee large-scale ML systems and improve user experience for over 500M users.

The AI Application Engineer will design and deploy AI systems, collaborate with teams, implement Generative AI solutions, and promote continuous learning in AI practices.

Lead the Opportunity Engine product development, managing cross-functional teams to drive advisor growth and improve client experiences using data and AI.

The role involves managing data to uncover insights, developing predictive models, and bridging clients with data intelligence within the context of evolving market research methodologies.

As a Senior Data Scientist, you will detect fraud, optimize payments, analyze data via A/B testing, and collaborate with various teams to enhance Lime's payments system.

Lead the design and implementation of advanced ML systems at Airbnb, mentoring engineers and shaping concepts into impactful products.

The Visiting Researcher will assist in developing ML models for healthcare applications, including NLP and predictive modeling, under mentorship in a focused research project.

The Business Development Director is responsible for acquiring new clients and expanding existing accounts, focusing on data, AI, and consulting services. Key duties include pipeline development, stakeholder engagement, revenue forecasting, and representing the company at industry events.

Lead the transformation of Clinical and Customer Operations at Hims & Hers by driving technology and AI strategy while managing teams, defining product vision, and ensuring alignment with business goals.

As a Senior Fullstack Engineer, you'll architect and build a high-concurrency auction engine, leveraging AI for enhanced user experiences and system reliability.

Lead evaluation and optimization of large-scale datasets for AI models. Design statistical methods, collaborate on data strategies, and enhance data quality.

As a Software Engineer at Speechify, you'll enhance AI Voice products, optimize ML pipelines, and improve deployment tools in a fast-paced environment.

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

Lead design and implementation of enterprise-grade AI systems, architect AI infrastructure, and drive technical strategy for AI-powered products primarily for military applications.

As a Senior Machine Learning Engineer, you will develop scalable ML solutions, collaborate with teams, optimize models, and implement best practices for deployments and infrastructures.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

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

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

The AI Data Specialist role involves data collection, evaluation, annotation, and tagging to support the enhancement of AI-generated content.