Machine Learning Jobs in Irving, TX

Leads user acceptance testing for agentic AI products within Consumer Small Business Banking Operations. Responsibilities include writing and executing test scripts, documenting results, creating user stories, preparing test data, developing test scenarios, facilitating end-to-end testing, reviewing requirements, and coordinating cross-functional initiatives and risk mitigation programs.

Design and deliver workforce analytics and predictive models using ML/AI. Acquire, clean, and explore structured and unstructured data, lead analytics projects, create visualizations, and communicate data-driven insights to business leaders to influence workforce decisions.

Leads user acceptance testing for agentic AI products within Consumer Small Business Banking Operations. Responsibilities include writing user stories, developing and executing test scripts, preparing test data, documenting results, reviewing requirements, coordinating testing, and supporting cross-functional programs, risk mitigation, efficiency, and customer experience initiatives.

Lead enterprise architecture for workforce technologies and related functions, driving AI adoption (Microsoft Copilot/Teams), platform strategy, integration, governance, and secure, compliant solutions. Manage a team of architects, partner with security, data, and business stakeholders, and promote AI-assisted prototyping and responsible engineering practices.

Validate and challenge in-house and third-party NLP, generative, and agentic AI models: review data and sampling, develop test models and reusable validation code, assess model performance and monitoring, write analytical reports, coach junior staff, and communicate with stakeholders, regulators, and auditors to ensure compliance with MRM governance.

Leads AI transformation across Citi Security and Investigative Services by identifying use cases, creating adoption roadmaps, building prototypes and proof-of-concepts, and partnering with Technology teams on production deployment. Designs AI-enabled workflows, integrations, automations, and agentic solutions using Python and enterprise AI platforms. Advises executives, drives adoption and change management, manages governance and risk requirements, and delivers measurable operational improvements and value realization.

Build AI-powered solutions for sales and marketing productivity, including LLM agents, NLP and Generative AI applications, recommendation systems, prompt and retrieval optimization, and agentic workflows. Prototype and evaluate AI capabilities, transition successful pilots into production, and collaborate with product managers, engineers, data scientists, and business stakeholders to deliver scalable solutions and measurable business outcomes.

Design, develop, test, debug, and maintain scalable applications using .NET, C#, and Angular. Build Azure data pipelines with Azure Data Factory and Databricks, manage Azure SQL databases, participate in architecture discussions, testing, code reviews, and Agile delivery. Address technical debt, communicate risks and dependencies, use AI-enabled development tools, stay current with technology, and begin mentoring associate engineers.

Serve as the Technical Product Owner on an Agile Scrum team, collaborating with architects, cloud engineers, and developers to maintain and prioritize the product backlog, define scope and roadmaps, craft customer-centric user stories, introduce technical innovations, and measure product performance to achieve business results.

Lead global marketing for Caris AI Insights, defining positioning, messaging, GTM, and commercialization. Drive product launches, sales enablement, thought leadership, customer evidence, competitive analysis, and cross-functional alignment to accelerate adoption of AI-driven oncology intelligence across healthcare, pharma, and research customers.

As a Data Scientist in the Innovation Team, you'll develop machine learning algorithms on molecular sequencing data to enhance cancer diagnostics and treatment, collaborating with diverse experts on high-impact projects.

Build platform-agnostic governance-as-code: intake APIs, automated risk scoring, SDKs, CI/CD-integrated governance checks, registry ingestion, audit artifacts, and runtime guardrails for AI agents.

Design and maintain data models and pipelines for mortgage and lending platforms. Develop ML/AI, predictive and prescriptive analytics, and LLM/Generative AI solutions. Collaborate with engineering and business stakeholders to build scalable cloud and data warehouse solutions, ensure data quality and governance, and deliver dashboards and executive reporting.

Leads Citi’s global Wealth Data and Analytics Production Management organization, overseeing up to 80 L1 and L2 support professionals across multiple regions. Owns operational stability, resilience, incident escalation, change governance, workload optimization, risk controls, budgets, vendors, and executive stakeholder relationships. Drives modernization through GenAI, automation, observability, SRE practices, self-healing capabilities, and disaster recovery improvements while developing a high-performing global team.

Designs and executes AI Quality Engineering strategies for enterprise AI applications, LLM solutions, intelligent automation, and agentic systems. Builds validation processes, evaluation frameworks, automated testing, runtime quality controls, observability, and reliability practices. Partners with engineering, clinical, security, governance, data, and product teams to validate healthcare workflows and responsible AI deployment. Coordinates Agile testing and release activities, supports production reliability, researches emerging technologies, and mentors Quality Engineers.

Develop automated analytics products and advanced data science solutions using machine learning, NLP, statistical modeling, predictive analytics, and generative AI. Lead end-to-end workflows from data preparation and experimentation through model validation, deployment, and visualization. Partner with product, engineering, and platform teams to move solutions from research into production, communicate findings to technical and non-technical audiences, and guide other data scientists.

Develop and deploy scalable data science products using machine learning, generative AI, NLP, statistical modeling, and predictive analytics. Analyze complex datasets, manage end-to-end modeling workflows, communicate insights through dashboards and presentations, and partner with engineering teams on production deployment. Provide technical guidance, apply responsible AI and model governance practices, and evaluate emerging technologies for business and clinical outcomes.

Leads the design, development, and deployment of advanced data science, machine learning, generative AI, and agentic AI solutions. Builds scalable analytics products, RAG systems, and evaluation frameworks; establishes technical standards and responsible AI governance; mentors data scientists; and partners with engineering teams to deploy and monitor production solutions. Translates complex analyses into actionable clinical, operational, and economic insights while guiding technical strategy and client-focused initiatives.

Lead architecture and development of scalable, secure systems; set engineering standards and CI/CD practices; mentor engineers; drive SRE/DevOps collaboration; adopt AI/ML tools; own incident response, root-cause analysis, performance optimization, IaC and cloud-native improvements; align technical roadmaps with product and business goals.

The HRIS Analyst administers and enhances Workday workforce management functionality, including reporting, dashboards, configurations, integrations, security, audits, data migrations, and troubleshooting. The role supports compliance, employee engagement, training, documentation, and process optimization while partnering with HR teams and business leaders. Required experience includes Workday administration, EIB and integrations, Excel-based data analysis, and strong communication skills. The position is hybrid in Irving, Texas and may require periodic travel and nonstandard work hours.

Serve as a bridge between business and technical teams to identify, design, validate, and support AI, automation, and analytics solutions. Gather and document requirements, translate business needs into AI use cases, support POCs and deployments, monitor model performance and KPIs, ensure responsible AI practices, and drive adoption through training, change management, and continuous optimization.

The Cybersecurity AI_ML Engineer develops and maintains security systems using AI and machine learning, implements threat detection, analyzes security metrics, and collaborates on security incidents.

Design, build, and maintain large-scale data infrastructure and pipelines (data lakes/warehouses). Integrate diverse data sources, optimize processing and queries, enforce data quality and security, implement monitoring/alerting, troubleshoot issues, and collaborate with cross-functional teams while exploring new data frameworks and cloud services.

Develop and execute data-driven marketing strategies that use AI, machine learning, and automation to drive brand awareness, customer acquisition, and revenue. Perform market research, competitive analysis, campaign optimization, CRM and marketing automation integrations, SEO/SEM and paid media optimization, dashboarding, and cross-functional collaboration with sales, IT, and product teams to measure and improve marketing ROI.

Lead strategic design, implementation, and scaling of Palantir Foundry/Gotham data solutions. Oversee cross-functional teams, manage full project lifecycle, deliver data integration, governance, analytics, and ML capabilities, and engage stakeholders and clients to translate business needs into scalable Palantir-powered solutions.