Machine Learning Jobs in North Las Vegas, NV

Leads the design, development, and deployment of scalable AI, generative AI, and machine learning solutions. Oversees data infrastructure, integration, data quality, and advanced analytics while managing client engagements and executive relationships. Drives business development, strategic direction, innovation, and AI-driven automation. Mentors teams, develops future leaders, and fosters collaboration, integrity, and client satisfaction across complex projects.

Leads Oracle Cloud Finance transformation workstreams, client engagements, and delivery teams across ERP and EPM programs. Designs finance processes, translates business requirements into Oracle Financials solutions, oversees configuration and deployment planning, and applies automation, analytics, and machine learning to improve finance operations. Manages risks, timelines, deliverables, and stakeholder relationships while coaching team members and identifying opportunities to improve budgeting, forecasting, reporting, and financial close processes.

Leads financial statement audits and evaluates governance, risk management, regulatory compliance, and internal controls for digital asset and financial services clients. Directs complex audit engagements, applies advanced auditing and technical accounting expertise, identifies material misstatements, and issues auditor reports. The role also involves client relationship management, coaching and developing diverse teams, communicating findings, and maintaining professional, independence, and ethical standards.

Leads client-facing generative AI and data modernization engagements, directing solution design, delivery planning, architecture, and technical decisions. Guides teams in prompt engineering, context engineering, agent orchestration, LLM evaluation, RAG, vector databases, and AI guardrails. Oversees cloud AI implementations using Gemini, Vertex AI, AWS Bedrock, or Azure AI Services; develops Python prototypes; evaluates model performance; manages workstreams and deliverables; and mentors staff on AI methods, agile delivery, and technical problem-solving.

Leads engineering teams delivering scalable AI and machine learning solutions on Google Cloud. Oversees generative AI architecture, Vertex AI, LangChain, LangGraph, LLM APIs, RAG, experimentation, evaluation, guardrails, and LLMOps. Guides technical strategy, client alignment, delivery execution, and team development while applying Python, data science, and machine learning methods to build reliable AI products.

Leads Google Cloud AI and machine learning engineering teams and client workstreams. Oversees generative AI, LLM application, agent orchestration, retrieval-augmented generation, model evaluation, prompt engineering, guardrails, and LLMOps initiatives. Reviews architecture, code quality, testing, and solution delivery using Vertex AI, LangChain, LangGraph, Python, and LLM APIs. Coaches team members, improves reusable delivery assets, and manages client relationships, timelines, quality, and expectations.

Leads client-focused generative AI and data modernization architecture, translating business needs into scalable solutions using Google Cloud, Vertex AI, LLMs, vector databases, and modern data platforms. Advises stakeholders, develops AI evaluation and guardrail practices, guides experimentation and deployment, presents technical recommendations, supports proposals, and coaches teams through complex transformation programs.

Lead complex data science and AI initiatives focused on healthcare affordability, medical cost management, and operational efficiency. Develop and deploy machine learning, causal inference, optimization, and AI solutions using healthcare claims and enterprise data. Guide architecture, governance, validation, and measurement of production models; mentor data scientists; establish technical direction; and communicate insights and business value to actuarial, clinical, business, technology, and executive stakeholders.

Develop and implement AI solutions and machine learning systems that enhance products and solve complex client problems. Responsibilities include advanced analytics, LLM production deployment, prompt engineering, RAG pipeline optimization, cross-functional collaboration, technical discovery, responsible AI advocacy, client relationship building, and mentoring junior team members.

Leads pricing and revenue data science initiatives for consumer markets clients. Develops predictive models, forecasts trends and customer behavior, manages dashboards and visualizations, ensures data quality, and translates complex analytics into strategic decisions. Oversees client engagements, validates outcomes, directs complex projects, and coaches diverse, high-performing teams.

Apply statistical and analytical methods to identify revenue opportunities, build predictive and explanatory models, design and evaluate experiments, analyze and integrate data sources, and translate findings into actionable recommendations for cross-functional stakeholders across hotel, F&B, pool, spa, and gaming operations.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Designs and develops scalable data pipelines, backend services, ETL/ELT workflows, APIs, microservices, and cloud-native applications using C#/.NET, SQL, Azure, and AWS. Responsibilities include database optimization, CI/CD, automated testing, DevOps, data governance, security compliance, and translating advanced technologies into production-ready healthcare solutions. Collaborates with research, engineering, and product teams while supporting ethical, performant, and reusable enterprise capabilities.

Manage a portfolio of 150–200 customer accounts across Canada and the U.S., building relationships, supporting retention, identifying expansion opportunities, and conducting customer meetings. Analyze usage data to recommend tailored solutions, reduce churn, resolve complex issues, and prepare business reviews. Collaborate with Sales, Solutions Engineering, and Product Development while serving as a primary customer contact and communicating technical value effectively.

Leads rigorous evaluation methodologies for autonomous vehicle performance using statistical analysis, machine learning, simulation, and on-road data. Develops metrics, detects drift and anomalies, identifies edge cases, correlates simulation with fleet data, and strengthens launch-readiness and safety decisions. Partners with engineering, safety, and operations teams, communicates findings to leadership, establishes developer self-service tools, and mentors colleagues.

Own product strategy and roadmaps across multiple products or segments, from customer discovery through launch and continuous improvement. Lead prioritization, solution validation, KPI and engagement metric frameworks, stakeholder alignment, and product feedback loops. Partner with UX, engineering, data science, project management, and leadership teams while mentoring product managers and advancing product management practices.

Leverage data science, machine learning, statistical analysis, and big-data techniques to solve business problems and support commercial strategy. Develop, deploy, and measure models, algorithms, automation, and analytical solutions. Collaborate with BI and enterprise data teams to improve reporting, visualizations, and data models. Present insights and recommendations to varied audiences while tracking business impact and evaluating emerging data engineering technologies.

Lead architecture and development of advanced perception systems for Level 4 autonomous vehicles. Build multimodal foundation models, synthetic data and sensor simulation capabilities, knowledge-distillation pipelines, and efficient real-time onboard models. Deploy solutions to autonomous vehicle fleets while mentoring engineers and providing technical leadership. The role focuses on object detection, segmentation, tracking, classification, sensor fusion, closed-loop evaluation, and robust generalization across vehicle generations.

Develop advanced machine learning, data mining techniques, predictive models, and analytical frameworks to identify and mitigate cybersecurity threats. Integrate cybersecurity data sources and sensor technologies, collaborate with cross-functional stakeholders, and deliver actionable insights supporting client and mission objectives. The role requires substantial cybersecurity and data science experience, leadership capability, strong communication skills, a Top Secret clearance, and relevant education or certifications.

Drives recurring-revenue growth across major enterprise fleet accounts through prospecting, consultative sales, strategic account planning, contract development, channel partnerships, upselling, and complex pursuit management. Maintains expertise in telematics and fleet management, analyzes market and competitive trends, supports forecasts, and collaborates with senior leaders and cross-functional teams. Requires frequent international travel and effective use of Salesloft, Salesforce, and AI-enabled selling tools.

Leads delivery, installation, maintenance, and lifecycle service operations for fleet, rental, or dealership customers. Owns SLA compliance, capacity planning, resource allocation, field-service team performance, vendor oversight, operational forecasting, and KPI achievement. Partners with Sales and Implementation to validate commitments and create executable plans while managing installation quality, costs, safety, utilization, and service outcomes.

Supports payer modernization and health services consulting engagements by analyzing operational challenges, optimizing processes, applying business analytics, engaging stakeholders, implementing quality standards, and guiding transformation initiatives. Develops operational support frameworks, conducts market research, manages change, and advises clients on improving service delivery and business performance while mentoring junior team members.

Drives new business growth in mobility data and analytics markets by identifying opportunities, developing strategic plans, building partner and reseller relationships, negotiating cooperative contracts, and managing sales pipelines. Conducts market and competitor analysis, supports RFX processes, develops sales targets and budgets, and collaborates with internal teams and leadership. Represents the company at trade shows and conferences while serving as a subject matter expert for partners and resellers.

Develops and oversees predictive analytics, automation, and reporting tools for aircraft reliability and maintenance. Analyzes flight, maintenance, component, and operational data; performs data mining, root cause analysis, anomaly detection, and predictive maintenance. Builds Skywise tools, electronic forms, automated reports, and relational datasets; reviews predictive alerts; coordinates with aircraft manufacturers, vendors, engineering, and maintenance teams; manages Skywise platform objects and access; and creates training and documentation.

The Director of Computer Vision will lead technical vision, research, and execution in developing scalable AI-driven computer vision solutions, managing teams, and enhancing performance metrics.