Top Machine Learning Jobs in Omaha, NE

The Hyperscalers and Commercial Lead will develop technology-driven business strategies, drive customer adoption, and manage end-to-end sales processes while working closely with cross-functional teams.

The role involves researching, developing, and implementing AI solutions, optimizing models, integrating AI into workflows, and collaborating with teams to enhance business efficiency.

Lead pre-sales technical engagements for Conversational and Generative AI solutions, collaborate across teams, and design value-driven demos for enterprise customers.

The Principal Architect will lead AI/ML solutions, mentor teams, and collaborate with clients to design and deliver scalable systems using Google Cloud technologies, ensuring compliance with ethical standards.

The Chief Architect will lead the technical direction for Legion's Workforce Management platform, focusing on architecture decisions, AI systems, and scalable software solutions. Responsibilities include hands-on coding, technical leadership, and ensuring systems meet enterprise standards for performance and security.

Lead the design, development, and deployment of scalable machine learning and AI systems for enterprise clients, guiding architecture and mentoring engineers.

Design, build, and deploy production-grade ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM applications, and scalable data pipelines with observability and MLOps practices for cloud and on-prem environments.

Leads data science strategy across Mexico and Brazil, manages and mentors a distributed team, and remains hands-on building and deploying machine learning models. Establishes modeling standards, infrastructure, delivery practices, and technical roadmaps while partnering with credit leadership on underwriting, valuation, impact measurement, and P&L analysis. Requires strong applied machine learning expertise, prior data science leadership, business communication skills, and understanding of credit or underwriting.

The Senior Machine Learning Researcher will design experiments, research new algorithms, and collaborate on deploying models for computer vision and robotics applications.

Leads enterprise sales strategy and revenue growth for AI-powered eDiscovery, legal technology, compliance, analytics, and data intelligence solutions. Builds pipelines, manages complex consultative sales cycles, develops executive client relationships, expands strategic accounts, and positions responsible AI adoption. Partners with product, operations, legal, security, marketing, and executive teams on solution development, pricing, contracts, implementation, and market expansion across corporations, law firms, government, and regulated industries.

As an AI Applications Engineer, you will bridge AI research and implementation, driving experiments, building infrastructure, and releasing products to improve user experience and metrics.

Leads technical solution development for military and federal health capture and proposal efforts. Designs secure cloud, DevSecOps, EHR modernization, interoperability, data, and analytics architectures; develops technical volumes, graphics, compliance matrices, staffing estimates, demonstrations, and presentations. Ensures security and compliance alignment, supports pricing strategy, collaborates across capture and delivery teams, and mentors architects and subject-matter experts.

Serves as the technical and business advisor for Verint’s Open CCaaS platform, selling CX automation solutions to C-suite customers. Builds executive relationships, communicates ROI, leads cross-functional product and sales teams, identifies expansion opportunities, and delivers thought leadership. Requires expertise in AI, data science, contact center operations, data architecture, and cloud platforms, with approximately 30–50% travel.

Lead Elastic’s strategy, vision, and multi-quarter roadmap for vector databases, embedding and reranking models, vector indexing, semantic ingestion, and search capabilities. Conduct market and competitive research, define product metrics, prioritize features, and partner closely with engineering, cloud, and applied research teams. Guide technical trade-offs involving recall, latency, index size, ingestion throughput, model lifecycle, and total cost of ownership across serverless and self-managed deployments.

Leads technology development for composite wind blade design, materials, manufacturing, tooling, and automation. Owns maturation from early research through production implementation, establishes technology roadmaps and stage-gate processes, and applies AI/ML to engineering and manufacturing challenges. Builds technical teams, manages budgets and partnerships, directs modeling and validation, supports production transitions, develops business cases, and protects intellectual property. The role collaborates globally with engineering, operations, quality, suppliers, customers, universities, and technology partners.

Own the end-to-end rebuild of Nextdoor’s consumer search experience, including query understanding, retrieval, ranking, result quality, organic and sponsored content blending, and monetization. Define search relevance metrics, partner with engineering, data science, ML, research, design, and marketing teams, and use A/B testing to improve engagement and revenue while protecting user experience.

Leads commercial, privacy, and product legal functions for a cloud technology company. Drafts and negotiates complex SaaS, partnership, reseller, and technology agreements; advises on global privacy, data protection, AI, intellectual property, and product development issues; develops contracting processes and playbooks; partners with cross-functional teams; and manages, mentors, and develops legal professionals.

Own the product strategy, roadmap, team, customer relationships, and P&L for Teamworks’ Coaching, Player Personnel, Recruiting, and Intelligence portfolio. Lead AI strategy across sports markets, integrate acquired products, align engineering, design, data science, marketing, and sales, and convert proprietary sports data into AI-powered workflows. Represent the business with teams, leagues, and partners while driving multi-market growth and product execution.

Design, train, and evaluate advanced machine learning models for autonomous driving, simulation, and ML platforms. Lead small cross-functional engineering teams, establish data and experiment practices for petabyte-scale training, address long-tail model failures, and work with multimodal datasets exceeding 100TB. The role requires commercial robotics experience, mentoring capability, expertise in VLA or generative world models, Python/PyTorch, sensor processing, and potentially edge deployment.

Leads Intermedia’s global accounting organization and financial reporting operations, including GAAP compliance, audits, tax, internal controls, revenue accounting, close processes, and business combinations. Partners with executive leadership on strategy, projections, growth initiatives, and operational improvement. Builds and mentors a high-performing global team while advancing technology-enabled automation and process efficiency across the CFO organization.

Leads technical sales and executive evangelism for Verint’s Open CCaaS and CX Automation platform. Acts as a trusted advisor to C-suite customers, articulating ROI, AI, data science, and platform capabilities. Partners with Product, Sales, Solutions, Services, Marketing, and Customer Success teams to drive adoption, expansion, thought leadership, and opportunity closure. Requires deep contact center operations experience, strong data architecture knowledge, executive communication skills, and extensive travel.

Design and deploy production ML/AI architectures on the Databricks platform, lead Generative AI (LLM, RAG, agent) implementations, optimize and scale MLOps pipelines, provide technical pre-sales support, and translate customer feedback into product improvements while mentoring peers and meeting delivery milestones.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

Source, engage, and qualify technical candidates using LinkedIn, GitHub, X‑Ray, and other tools. Build pipelines for engineering and technical leadership roles, run outreach campaigns, perform initial screening, document candidate details in ATS/CRM, and partner with recruiters to meet client hiring timelines while improving sourcing strategies.