Top Senior Machine Learning Jobs in Lincoln, NE

Design and implement software solutions for machine learning operations, focusing on geospatial imagery analytics and MLOps software development.

The Machine Learning Engineer III will design, develop, and deploy machine learning models and algorithms, mentor junior staff, and collaborate with cross-functional teams to solve complex business problems.

Design and build recommendation and personalization systems, conduct A/B testing and causal inference, and mentor the data team in best practices.

The Sr. Staff Machine Learning Engineer will lead architecture and development of ML systems, enhance patient interactions, optimize treatment recommendations, and mentor engineers.

The Senior Machine Learning Engineer will design and maintain ML solutions for fraud detection, collaborating across teams and establishing MLOps best practices.

The role involves developing cloud solutions and enhancing ML/AI pipelines, ensuring service availability, and automating deployments in a scalable environment.

Develop and optimize machine learning models for processing financial documents, mentor junior staff, and collaborate across teams to enhance software products.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

As a Senior Software Engineer in Machine Learning, you'll develop and maintain machine learning models for geospatial analytics, collaborate with teams to refine algorithms, and ensure high-quality deployment of models at scale.

You will take ownership of ML Ops systems, improve CI/CD processes, and enhance software infrastructure for ML Engineers providing real-time intelligence products.

The role involves developing advanced machine learning solutions, collaborating with experts, and managing ML model architecture and deployment.

The Senior Staff AI/ML Engineer will design, develop, and deploy scalable machine learning models, collaborating with teams to address business challenges and ensure high performance in production environments.

As a Staff Machine Learning Engineer, you will develop, productionize, and deploy ML models for clinical use, ensuring real-world effectiveness through hands-on coding and infrastructure building.

Lead design and development of AI/ML demos on Snowflake platform, collaborating with product teams to align with releases and providing technical expertise in data science and MLOps.

The Machine Learning Engineer will develop AI products by designing and deploying ML models, optimizing pipelines, and collaborating with teams.

The Senior ML Engineer will design evaluations for AI features, optimize pipelines, and ensure quality in ML systems while collaborating with cross-functional teams.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

As a Senior Data Scientist, you will develop models to extract insights from complex datasets, focusing on temporal and geospatial features, while collaborating with engineering teams to implement solutions.

Collaborate to scale self-driving systems, build training frameworks, profile model performance, and evaluate emerging technologies for training and inference.

Lead the design and deployment of scalable ML infrastructure, focusing on MLOps and LLM strategies, while mentoring team members and ensuring operational maturity.

Lead ML Performance Optimization for autonomous driving, collaborating across teams, implementing optimization techniques, and mentoring engineers for career growth.

As a Senior Machine Learning Engineer, you will build and productionize ML models, develop scalable infrastructure, and mentor teams to optimize marketing products.

As a Senior Machine Learning Engineer, you will design and deploy object detection models, collaborate with teams, and enhance ML solutions.

The role involves designing and implementing cloud-native infrastructure for AI/ML workloads, optimizing Kubernetes environments, and contributing to open-source MLOps tooling.

Lead a team of data scientists developing ML-driven products, managing infrastructure, training models, and ensuring production quality while collaborating with senior leadership.