Top Remote Machine Learning Jobs in Lincoln, NE

The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.

Design, architect, and deploy generative AI/LLM solutions from prototype to production; work directly with clients to translate business needs into technical plans; write production-quality code integrating LLMs and ML models; collaborate with cloud, DevOps, and frontend teams; support proposals, sales, and evaluation/observability of models.

The Technical Product Manager will define roadmaps for an AI Platform, manage ML systems, partner with engineers, and improve healthcare outcomes.

The role involves building AI technologies for customer service, developing ML systems, and collaborating with cross-functional teams to enhance user experiences.

The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.

Design, build, and maintain forecasting and portfolio optimization models for U.S. power markets; analyze market outcomes, track supply/demand/congestion dynamics, and apply statistical, optimization, and ML methods to inform commercial decisions.

The Director of AI will lead AI and machine learning initiatives, develop AI architecture for humanoid robots, oversee production-ready AI systems, and manage team growth and budget.

The Product Operations Associate will support the development of AI-driven products by ensuring accuracy, documentation, and effective workflows, while collaborating with various teams.

Lead the development of AI-powered tools and products, manage product roadmaps, collaborate cross-functionally, and drive innovation in media and advertising.

Lead Yahoo's Data Activation product area: define vision and strategy, partner with Data Science and Engineering, drive cross-vertical data activation initiatives, deliver measurable business impact, and mentor/manage product teams to execute on audience, personalization, and targeting use cases.

The Senior Data Scientist will design, develop, and own machine learning systems for document verification focusing on computer vision and deep learning. Responsibilities include technical leadership, engaging with customers, and collaborating with engineering and product teams.

The Machine Learning Associate will curate and validate data, generate synthetic datasets, optimize algorithms, and analyze accuracy for machine learning models in retail contexts.

As a Machine Learning Engineer, you will own the full lifecycle of ML from model development to production deployment, collaborating with teams to drive ML processes.

The role involves designing and supporting GPU/Kubernetes clusters for AI/ML workloads, developing automation tools, and troubleshooting infrastructure issues.

As a Senior Technical Recruiter for AI/ML, you'll manage full-cycle recruiting for senior AI roles, build talent pipelines, and partner with leadership to close top talent effectively.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

The Data Scientist will analyze and model data related to ad-tier members, focusing on identity modeling and improving ad targeting capabilities, while collaborating with cross-functional teams.

The Manager, Growth Analytics & Marketing Science will build and evolve marketing measurement frameworks, drive analytics, and optimize marketing strategies through data and AI.

The Senior Product Manager will lead the pricing and valuation engine, overseeing ML modeling, pricing systems, and improving valuation accuracy while managing cross-functional roadmaps and execution.

Co-found and lead a stealth startup building an agentic AI platform embedded in CAD tools to automate geometry updates, feature-tree edits, and cross-tool workflows. Drive product, engineering, and commercial strategy, hire the founding team, and develop a defensible data capture and automation stack for industrial CAD workflows.

This role leads the ML Acceleration team, focusing on enhancing ML model training efficiency and team management, while driving technical strategy and collaboration.

The Data Scientist will develop predictive models, analyze geophysical data, and collaborate with geoscientists to enhance exploration programs, focusing on mineral deposits.

Lead end-to-end design and registration of agricultural soil carbon projects, interpret and implement VCS methodologies, design soil carbon sampling and GHG measurement strategies, prepare and defend project documentation, embed methodological rigor into products and processes, train staff, advise leadership on risk and strategy, and represent Perennial in registries and industry forums.

The Research & Development Clinical Pathologist will collaborate on innovative solutions in veterinary medicine, leveraging technology and clinical pathology expertise.

Lead the advancement of embedding-based retrieval systems, focusing on multimodal models, model performance, and extensibility for various use cases.