Top Remote Machine Learning Jobs in Omaha, NE

The AI/ML Specialist Solution Architect Intern will assist in designing AI solutions, learning about distributed workloads, and preparing technical materials, gaining mentorship and exposure to modern ML frameworks and GPU infrastructure.

The Senior Analyst in Predictive Analytics and Machine Learning develops and maintains statistical models to support business decisions, monitors model performance, and collaborates with stakeholders across the company.

As a Senior ML Engineer for Payments, you will develop AI solutions for payment experiences, optimize transaction processing, and ensure system reliability while mentoring teammates and collaborating with cross-functional teams.

The Senior AI Engineer will develop AI solutions for incident management, collaborate cross-functionally, and enhance observability tools through iteration and ownership.

Design and implement production-grade ML systems for ICS/OT cybersecurity, build and optimize models (including NLP/LLMs), develop data pipelines and MLOps workflows, collaborate with data teams to deploy and monitor models in cloud and on-prem containerized environments, and troubleshoot production performance and resource issues.

The Applied Scientist AI/ML Intern will work on building data pipelines, finetuning LLMs, and deploying AI models in a collaborative team environment.

As a Senior AI/ML Engineer, you will design and develop advanced AI solutions for finance, focusing on ML and GenAI, ensuring compliance and operational efficiency.

Lead the design and operation of Twilio's ML and data platform, architecting cloud-native pipelines and implementing MLOps best practices while mentoring engineers and collaborating across teams.

Manage and mentor a team of machine learning and data engineers, overseeing ML model development, data pipelines, and collaborating with product teams on technical requirements.

The Machine Learning Engineer will develop and optimize models for processing tax documents, mentor juniors, and collaborate across teams.

The MLOps Engineer will design scalable ML infrastructure, manage containerized environments, develop training pipelines, and implement CI/CD pipelines, ensuring model reliability and performance.

Develop and deploy AI agents, integrating them with external systems and optimizing performance in multi-agent environments. Collaborate with product managers to align agent capabilities with business needs, exploring technologies in Generative AI and LLM orchestration.

The Staff Machine Learning Engineer will lead ML initiatives, develop AI systems, optimize pipelines, and mentor team members to automate healthcare processes.

The Machine Learning Scientist will design causal inference models, build measurement pipelines, and collaborate with Finance & Product teams to optimize subscription pricing strategies at Netflix.

As a Machine Learning Scientist, you will build and enhance forecasting models for Netflix's subscription business, collaborate with various teams, and improve statistical forecasting methods while considering external market signals.

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.

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

Design, build, and scale ML and Generative AI systems. Develop applications using ML architectures and monitor model performance.

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.

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 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.

The Staff Machine Learning Engineer will develop AI/ML applications, collaborate with teams to implement models, and leverage a variety of technologies to enhance Twilio's customer support operations.

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 Staff Product Manager will collaborate with research, engineering, and design teams to develop AI tools, define metrics, and enhance existing products based on user feedback and testing.