Top Remote Machine Learning Jobs in Lincoln, NE

Lead ML strategy and standards as a senior individual contributor: define ML infrastructure, tooling, and lifecycle processes; establish monitoring and feature patterns; partner across platform, data, and product teams; mentor data scientists and ML engineers to scale reliable production ML systems.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.

As an MLOps/ML Platform Engineer, you will build and manage ML systems, optimize workloads, and ensure production model reliability while collaborating across teams.

The Senior Product Manager will lead the strategy for an AI assistant, ensuring compliance and user satisfaction while coordinating with cross-functional teams throughout product development.

The Sr. Machine Learning Engineer will build tooling and services for ML and generative AI solutions, focusing on deployment, evaluation metrics, and cross-functional collaboration.

As a Software Engineer, AI/ML GenAI, you will design and implement AI features, manage embeddings, and optimize AI systems for production deployment while collaborating with product and design teams.

The role involves designing and implementing data and AI architectures, developing data pipelines, and integrating machine learning solutions while fostering Agile methodologies and collaboration.

As an AI/ML Engineer, you will design, train, and deploy machine learning models, optimize model performance, and collaborate with cross-functional teams to integrate AI capabilities into products.

The Machine Learning Engineer will work on sensing and perception algorithms, deploying computer vision algorithms, and collaborating for code testing and evaluation.

Lead research on humanistic AI for autonomous systems. Collaborate with teams, design experiments, and publish findings in top-tier publications.

Convert data science prototypes to production-grade ML tools, deploy and monitor models, run and interpret tests, manage ML platforms, identify data drift, evaluate vendor AI solutions, and communicate technical findings to varied audiences.

Build AI/ML-powered features across ClickHouse Cloud, designing scalable APIs, integrating inference systems and vector DBs, implementing frontend interfaces, and ensuring production-grade monitoring, versioning, and observability for model deployments.

The Senior Machine Learning Engineer will build and operate ML systems, manage the model lifecycle, and mentor team members while ensuring sustainability data accuracy.

As a Senior Machine Learning Scientist, you will design, build, and optimize deep learning models for biological data analysis, ensuring high-quality outputs and leading complex projects from conception through deployment.

As a Machine Learning Engineer, you'll architect data pipelines, build ML training workflows, integrate event streams, and collaborate with teams to improve model performance and ensure compliance.

This internship focuses on clinical pharmacology and AI/ML modeling, providing experience in developing predictive models using clinical datasets.

As a Full Stack Engineer, you'll develop production-ready AI and ML features, build APIs, design scalable systems, and implement frontend solutions using Angular.

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

Build a next-generation ML data and feature infrastructure platform to enhance the productivity of ML practitioners and improve feature accessibility.

Join Netflix's Algorithms team as a Machine Learning Software Engineer to design and develop solutions for personalization systems. Collaborate on scalable machine learning algorithms and enhance software engineering practices.

As an ML Engineer, you will build and productionize predictive models for ad inventory and campaign performance, contributing to the growth of Netflix's ad platform.

The Machine Learning Engineer will execute the full ML lifecycle, collaborating on model implementation and improving customer experiences through data-driven insights.

Design and implement ML infrastructure for scalable deployment, collaborate across teams, optimize ML systems, and enhance tooling.

Drive cross-team engineering efforts to improve user experience on Homefeed by implementing large-scale machine learning systems and enhancing data processing efficiency.

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