Machine Learning Jobs in Richardson, TX

Develops enterprise strategy and adoption programs for AI, automation, workflow, and business process technologies. Evaluates emerging capabilities through proofs of concept, coordinates technology teams and vendors, influences platform roadmaps, and creates executive communications. Leads learning, enablement, certification, and training programs to build organizational capability across business lines. The role requires strategic analysis, program management, executive engagement, and the ability to translate emerging technologies into scalable business value.

Supports HBM architecture research through AI workload analysis, performance modeling, simulation framework development, and trend dashboard creation. The intern analyzes bandwidth, latency, and memory requirements, researches compute and infrastructure trends, and collaborates with technical mentors on next-generation AI memory systems.

Lead the design and implementation of Generative AI solutions for complex business challenges. Collaborate with data scientists, engineers, and product managers; conduct research; build prototypes; demonstrate concepts; oversee data processing and model development; and support implementation and optimization. Translate stakeholder needs into technical requirements, manage cross-functional relationships, communicate AI concepts, and apply project management practices to estimate timelines and coordinate dependencies.

Owns the Trade and Working Capital AI use-case portfolio from ideation through delivery and value realization. Translates business needs into technical requirements, prioritizes opportunities, coordinates with AI, data science, technology, data, and infrastructure teams, and drives adoption across product, commercial, and productivity applications. The role also leads AI literacy initiatives, aligns business priorities with enterprise governance and AI programs, manages multi-workstream delivery, and reports progress and realized value to senior stakeholders.

Develop Generative AI solutions for financial services using Python, PyTorch, LangChain, AWS, Spark, vector databases, multi-agent systems, and advanced RAG pipelines. Build, fine-tune, evaluate, validate, and deploy machine learning models across large numeric and textual datasets. Collaborate with data scientists, machine learning engineers, and product managers while translating technical findings into business outcomes.

Supports Finance and cross-functional teams by building data pipelines, improving data quality and governance, automating reporting, developing Power BI dashboards, applying AI and analytics, and contributing to financial models, forecasts, reconciliations, and executive insights.

Leads Card customer analytics and AI strategy, overseeing analytics leaders, data scientists, and analysts. Drives GenAI, machine learning, experimentation, personalization, competitive intelligence, and forward-looking analysis across product, pricing, marketing, and servicing. Partners with business and technical stakeholders to deliver responsible solutions from concept through production, while building organizational capabilities, developing talent, and influencing executive decisions.

Leads data ownership and governance for data products, defining metadata, quality, controls, integration, and risk mitigation. Partners with business, analytics, technology, and engineering teams to deliver curated datasets and production-ready solutions. Uses advanced SQL for validation and root-cause analysis, manages workstreams and staff, and supports analytics and machine learning use cases. Applies AI and LLM tooling to automate governance activities and maintains data integrity across regulated environments.

Designs and delivers enterprise workflow automation, AI, process mining, and intelligent document processing solutions. Partners with stakeholders to identify automation opportunities, gathers requirements, develops and tests solutions, and manages deployment and post-production support. Uses Pega, Power Platform, UiPath, Alteryx, Python, Signavio, and AI technologies to improve operational efficiency, employee experience, compliance, and measurable business outcomes.

Leads security engineering across multiple technology domains, clarifies security requirements, supports multi-level network security, and advises stakeholders during vulnerabilities and disruptive events. Performs threat modeling, risk assessment, vulnerability and penetration testing, and validates AI-assisted security recommendations. Designs and implements enterprise security solutions while ensuring security testing, control validation, traceability, auditability, and resiliency throughout software development lifecycles and toolchains.

Designs, develops, deploys, and optimizes AI and machine learning solutions for business and technical challenges. Responsibilities include anomaly detection, predictive maintenance, root-cause analysis, chatbot operations, digital-twin development, closed-loop simulations, model evaluation, cloud deployment, and cross-functional integration. The role also researches emerging AI techniques, analyzes data, documents architectures, and troubleshoots conversational agents.

Leads data science work for personalized recommendation systems, partnering with engineers and product managers to deliver customer-facing products. Builds and deploys machine learning models across design, training, evaluation, validation, and implementation using large-scale data. Applies advanced methods including recommender systems, reinforcement learning, causal inference, transformers, and foundation models. Translates complex analyses into business outcomes while developing talent and guiding technical strategy.

Lead cybersecurity architecture for cloud-native enterprise solutions: evaluate controls and new technologies, advise stakeholders, provide technical guidance, promote firmwide SDLC practices, and mentor peers to mitigate risk and adopt strategic solutions.

Leads endpoint detection engineering using AI, machine learning, Detection-as-Code, behavioral analytics, and MITRE ATT&CK. Owns detection coverage from telemetry onboarding through alert deployment, tuning, and gap analysis. Partners with threat intelligence, security operations, and business stakeholders to manage cyber risk and compliance. Conducts threat research, aligns detection capabilities with red-team techniques, mentors engineers, and drives architecture decisions for scalable, high-fidelity endpoint protections.

Lead the strategy and delivery of AI-ready data products within Card Data & Analytics. Partner across data platform engineering, analytics engineering, AI/ML, product, governance, risk, and controls teams to improve data quality, modeling, discoverability, lineage, documentation, privacy, and readiness. Translate business needs into governed data products, shape roadmaps, prioritize investments, drive execution across complex initiatives, and communicate outcomes to technical and executive stakeholders.

Own the strategy, roadmap, and delivery of Applicant Security products addressing identity fraud, resume fraud, bot activity, and abuse. Partner with engineering, data science, cybersecurity, legal, HR, and vendors to define requirements, prioritize backlogs, manage releases, establish success metrics, and ensure privacy and compliance. Lead third-party security vendor evaluation and governance while balancing risk reduction with candidate experience in a complex enterprise environment.

Leads control management for JPMorganChase’s Consumer and Community Banking Operations portfolio. Designs and strengthens risk and control frameworks, identifies emerging compliance and operational risks, drives governance and issue management, and promotes consistent agile control practices. Partners with Product, Technology, Legal, Compliance, Audit, and Risk stakeholders to support transformation initiatives, regulatory compliance, control effectiveness, and operational resilience. Requires strong risk-based decision-making, change management, stakeholder influence, executive communication, and data literacy.

Leads full-stack software engineering and infrastructure platform development for AI-driven, self-healing data center operations. Designs Java, Python, and Node.js applications, scalable APIs, CI/CD automation, cloud-native platforms, VMware integrations, and infrastructure-as-code workflows. Develops machine learning models for forecasting, anomaly detection, and test classification, integrating them into operational systems for predictive alerts and workload orchestration. Provides technical leadership, mentors engineers, reviews code, and drives firm-wide architecture and technology decisions.

Lead design-driven technical solutions that blend UX and software development. Create service flows, wireframes, prototypes, and CX strategies; guide technical teams and integrate user research, AI, and accessibility into products.

Lead architecture strategy and roadmaps for cloud-based, AI-enabled payment systems. Advise on technology selection, build reusable secure engineering patterns, develop and review production code, govern APIs and integration patterns, and drive digital transformation for onboarding and self-service experiences.

Designs, deploys, maintains, and troubleshoots HPE NonStop payment infrastructure, secure key managers, Etinet servers, and related subsystems. Uses AIOps and AI-assisted practices for incident triage, anomaly detection, automation, documentation, and reliability improvements. Partners with SRE, observability, and cybersecurity teams to govern AI-enabled monitoring, maintain auditability, execute upgrades, and produce operational knowledge such as runbooks and troubleshooting guides.

Lead architecture for global cloud-based eCommerce payment platforms. Advise stakeholders on design and technology selection, define multi-year roadmaps, apply AI-enabled architecture patterns, ensure security/compliance, evaluate vendors, and present strategies to senior leaders to modernize merchant acquiring, payment gateway, and developer-facing APIs.

Own the vision, strategy, roadmap, backlog, metrics, and end-to-end delivery of enterprise contact center capabilities. Integrate Amazon Connect workflows with business applications, lead discovery and stakeholder alignment, manage product readiness and adoption, and ensure secure, reliable, measurable outcomes across engineering, operations, risk, and business teams.

Lead architecture design and governance for trade surveillance products, provide technical direction, integrate enterprise AI securely and auditable into architectures, develop and review production code, and establish reusable SDLC/toolchain patterns.

Lead enterprise payments architecture for card-present solutions, provide technical governance and guidance, integrate AI-enabled capabilities securely, develop and review production code, evaluate emerging technologies, and drive architecture decisions across product families.