Top Machine Learning Jobs in Omaha, NE

Lead development of new credit line management programs by designing, testing, and scaling policies. Own end-to-end analytical work using SQL/Python, partner with Data Science and Product, and present data-driven recommendations to senior stakeholders to improve spend recovery, utilization, and line-management performance.

The job involves selling AI and Machine Learning technologies to mortgage companies, managing the sales process for enterprise customers, and working with remote teams.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions, architect scalable infrastructure, and implement data pipelines across multi-cloud environments while collaborating with cross-functional teams to maximize business value.

Lead the integration of AI and digital solutions in manufacturing processes, driving adoption and measurable impact on efficiency, quality, and performance.

The Staff Machine Learning Engineer will lead AI initiatives, architect LLM systems, design evaluation frameworks, and mentor engineers.

As a Senior Machine Learning Engineer, you will enhance diffusion models, conduct research, collaborate on system implementations, and communicate findings effectively.

As a Principal Solutions Architect, you will oversee technical architecture for VA IT modernization, writing prototypes, guiding engineering teams, and representing Credence to VA stakeholders. You will also contribute to capture strategy and mentor engineers on compliance and integration.

The Principal Product Manager - Growth will lead growth initiatives, focusing on user engagement, retention, and the use of AI to enhance product strategies and experiences.

Design, build, and deploy machine learning systems for controlling quantum processors. Develop reinforcement learning and Bayesian methods for QEC calibration, and work cross-functionally with product and R&D teams.

The Senior Technical Architect will lead AI SDLC transformations, create architectural solutions, mentor teams, and drive innovation in regulated industries.

As a Regional Sales Director, you'll lead a sales team, develop business plans, and drive sales growth by managing complex cycles and nurturing talent.

Provide on-call MLOps support for machine learning teams by triaging pipeline issues, debugging workflows, identifying root causes, and maintaining reliable model development operations. Collaborate with senior engineers to improve tooling, documentation, and processes, while communicating technical findings across teams. The role requires Python, foundational PyTorch and model pipeline experience, plus familiarity with CI/CD, monitoring, logging, and orchestration tools.

Own the full lifecycle of clinical text extraction models, from problem framing and annotation strategy through production deployment, evaluation, monitoring, and retraining. Build clinical NLP pipelines, establish defensible quality and error-analysis systems, and apply LLMs using rigorous evaluation, observability, and cost controls. Partner with clinical data and backend engineering teams while addressing PHI protection, de-identification, auditability, and access controls. As the first ML hire, set technical direction and potentially build and lead the future ML team.

Lead end-to-end product strategy and delivery for a core marketplace area, collaborating with engineering, UX, and design. Conduct qualitative and quantitative research, run agile sprints, measure results with analytics, and pioneer AI/ML product features and workflows to improve user experience and platform impact.

Lead go-to-market for Mapboxs AI products: define positioning, messaging, and launch strategy; drive customer research, sales enablement, content, and cross-functional alignment to accelerate adoption of AI-powered location capabilities.

Lead development and application of analytics, statistical models, and dashboards to support R&D Quality oversight. Integrate clinical, safety, lab, and operational data to identify risks, support audit/inspection readiness, enable RBQM, and provide actionable quality insights and recommendations to cross-functional partners.

Lead strategic vision and execution of next-generation bioinformatics technologies. Identify and evaluate emerging computational methods, translate research into production-grade pipelines and prototypes, support product roadmaps and technology transfer, and partner cross-functionally to commercialize genomic and AI-driven healthcare solutions.

Lead pricing and monetization strategy across global markets. Design pricing models and packaging, optimize discounting and payments economics, apply AI/ML analytics to drive revenue and margin, partner cross-functionally with Product, Sales, Finance, and Revenue Operations, govern pricing changes, and enable sales with pricing tools, policies, and training to improve ARR, retention, and profitability.

Provide senior legal and regulatory counsel for digital health and medical device products (SaMD), guiding product lifecycle, FDA and global filings, AI-enabled features, labeling, compliance, post-market obligations, and cross-functional governance. Lead strategy, manage external counsel, and translate regulatory developments into business guidance.

Develop and scale machine learning training systems for robotics data, optimize training pipelines, and collaborate with ML researchers to enhance autonomy models.

Lead design, development, and production deployment of ML and algorithmic solutions. Own end-to-end ML systems, support distributed production reliability, communicate tradeoffs, and apply generative AI, LLM fine-tuning, RAG, and agentic techniques to product problems.

Senior individual contributor responsible for leading pet/P&C insurance pricing model development (GLMs and ML), owning end-to-end projects, performing EDA and root-cause analysis, communicating results to stakeholders, and mentoring junior team members.

Responsible for fine-tuning state-of-the-art LLMs, optimizing models for deployment, and driving AI architectural decisions. Collaborate with cross-functional teams to develop impactful AI products.

Build and maintain scalable ML and generative AI platforms and backend infrastructure; deploy and manage production applications; create services exposing ML/AI products; implement RAG solutions and vector databases; integrate LLM orchestration and foundation model APIs; collaborate cross-functionally and mentor teammates.

Lead development of an AI-enabled Ethereum Layer 2 platform: build front-end and back-end systems, deploy and optimize AI models, create data pipelines, collaborate on model training, and contribute to product innovation and other company projects.