Top Remote Machine Learning Jobs in Lincoln, NE

As a Senior Data Scientist, you will analyze data, build models, and collaborate with teams to enhance credit evaluation using machine learning.

The Principal Product Manager will define and execute the product roadmap for the Data and AI Platform, collaborating with engineering and sales to develop AI-powered identity security solutions.

As a Sr. Machine Learning Engineer, you'll develop ML solutions for healthcare, manage data pipelines, write production-ready software, and own ML services end-to-end.

The Senior Machine Learning Engineer will design and optimize ML models, manage end-to-end ML projects, and enhance SailPoint's AI capabilities while collaborating with various teams to integrate AI features into products.

Develop and productionize a next-gen Dispatch System, build predictive models, automate processes, and lead a small team in optimizing operations.

Responsible for designing and implementing AI solutions across cloud platforms, leveraging Generative AI, and managing AI services, pipelines, and infrastructure.

Lead the development of ML solutions to enhance user experience at Babylist. Build recommender systems and personalization features from scratch, collaborating with a cross-functional team.

Lead centralized Machine Learning efforts at Affirm, managing model development lifecycles, fostering AI adoption, and overseeing a team of ML professionals to enhance business outcomes.

As a Machine Learning Security Researcher, you will conduct research on security for machine learning systems, develop security frameworks, and engage with AI organizations to assess and improve their security posture.

Design and build a machine learning platform, deploy ML models, collaborate across teams, and establish monitoring standards for AI solutions.

As a Staff Machine Learning Engineer, you will lead the design, implementation, and optimization of machine learning models, collaborate cross-functionally, and drive AI strategy to enhance SailPoint's identity security solutions.

Design and implement machine learning pipelines for fraud and payment systems, collaborating with data scientists and engineers to enhance reliability and decision-making.

Develop and productionize a next-gen Dispatch System, build ML models, automate processes, and collaborate with various teams while mentoring other engineers.

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

The Senior Machine Learning Platform Engineer will optimize ML infrastructures, mentor junior engineers, and raise engineering standards for ML models and systems.

The Senior Machine Learning Engineer will design, build, and lead strategies for risk detection models, mentor team members, and apply advanced AI/ML methodologies to enhance user security and experience.

Lead the design and implementation of AI/ML models for risk and fraud detection at Coinbase. Collaborate with teams to develop scalable systems, mentor engineers, and ensure effective AI/ML solutions align with company goals.

Design and deploy machine learning algorithms, develop production systems, and collaborate with stakeholders to align ML solutions with business objectives.

The Principal Product Manager will oversee AI/ML initiatives, drive product development, translate strategy into technical specs, and manage product lifecycle.

The VP Analyst will conduct in-depth research on AI technologies in Cloud IT services, develop market insights, engage clients, and contribute to thought leadership.

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.