Top Machine Learning Jobs in Lincoln, NE

Develop and optimize unimodal and multimodal perception models for 3D/BEV terrain and surface inference, build large-scale data pipelines and annotation tools, deploy and optimize models on edge compute, collaborate with robotics/software/hardware teams, mentor juniors, and translate research into production-grade autonomous vehicle perception systems.

Lead design, training, and iteration of diffusion-based generative models producing 3D geological models conditioned on geophysical and borehole data; curate synthetic and real datasets; adapt models for projects and collaborate with teams.

As a Product Manager, you'll transform data into opportunities, manage technical product development, and foster cross-functional collaboration for philanthropic initiatives.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

The Senior Machine Learning Operations Engineer will design, build, and maintain ML infrastructure, streamline model deployment, and monitor performance to ensure the success of machine learning models at The Athletic.

As an AI/ML Data Engineer, you will design and build data and ML infrastructure to create personalized student experiences, working on ETL processes, feature stores, and collaborating with product and data science teams.

This role involves deploying and optimizing machine learning models for autonomous vehicle motion planning, ensuring performance and reliability in production settings.

Lead the technical vision and architecture for machine learning and data systems, overseeing scalable infrastructure and collaboration across teams.

As a Machine Learning Engineer, you'll build AI solutions from structured leadership data, develop RAG-based agents, and enhance the Leadership Intelligence Platform, focusing on efficiency and collaboration with research partners.

Lead computer vision projects and develop ML models for power grid analysis while mentoring engineers and ensuring software quality standards.

The Senior Machine Learning Operations Engineer will build and operationalize the ML Ops platform to deploy and monitor machine learning models, focusing on infrastructure, automation, and integrating ML workloads within the AWS-native architecture.

Lead development of cutting-edge Machine Learning models and infrastructure for search and recommendations at Airbnb. Collaborate with cross-functional teams on impactful projects using large-scale data.

Lead the implementation of generative AI and machine learning solutions, focusing on architecture, governance, and collaboration with teams to ensure compliance with AI standards.

Responsible for building and maintaining end-to-end ML pipelines and deploying production-grade ML systems. Tasks include model fine-tuning, evaluation, and collaboration with engineering teams.

The VP of Research, Machine Learning will set research direction for AI systems, focusing on context representation, reasoning, and evaluation frameworks while ensuring product safety and alignment.

The Senior Machine Learning Engineer will design and implement ML solutions, collaborate with teams, and contribute to scalable infrastructure enhancements.

The role involves designing and developing machine learning infrastructure and models, consulting on best practices, and building scalable services for AI integration.

As a Senior Machine Learning Engineer, you will design ML infrastructure, build AI features, and collaborate with cross-functional teams while managing large data sets.

Develop, evaluate, and deploy AI systems and machine learning models, focusing on NLP and multimodal models. Collaborate with teams and publish research.

Design and implement a perception system for autonomous vehicles, focusing on data integration from various sensors and ensuring safe operation.

The Lead AI/ML Engineer evaluates emerging technologies, leads teams in adopting solutions, and provides technical leadership while mentoring junior specialists.

The role involves delivering advanced analytics and machine learning solutions, collaborating with stakeholders, and mentoring junior data scientists.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

The Machine Learning Engineer will design, develop, and deploy ML models using Google Cloud tools, focusing on Document AI and Vertex AI, ensuring scalable applications and efficient performance.

Develop and maintain web-based tools for AI/ML practitioners, improve model observability, enhance user experience, and collaborate cross-functionally. Drive product excellence and improve systems and codebase.