Machine Learning Jobs in Richardson, TX

Lead and mentor an agile engineering team to design, build, test, and operate secure, cloud-native production software. Provide technical direction, deliver high-quality code, drive product design decisions, and advocate firmwide engineering practices while applying AI/ML expertise.

Support cybersecurity incident response, monitoring, threat intelligence, and threat hunting. Develop automation, scripts, and AI-enabled tools to improve detection and investigations. Build metrics, dashboards, and collaborate with IT, legal, privacy, and business stakeholders to strengthen security operations.

Leads software engineering for large-scale big data and cloud-native platforms within risk technology. Responsibilities include designing and deploying AWS solutions, migrating legacy applications, developing secure production code, supporting operational stability, and guiding engineers, vendors, and technical teams. The role drives AI-assisted engineering governance, automation, testing, monitoring, and reuse across the software development lifecycle. It also requires expertise in Python or Java, machine learning, data pipelines, Spark, Databricks, and cloud technologies.

Lead and grow multiple product-focused software engineering teams building cloud-native, ultra-low-latency, highly resilient payment systems. Drive architecture, microservices decomposition, AWS deployments, engineering practices, cross-team collaboration, mentorship, and adoption of cutting-edge AI tooling to accelerate development and improve system availability and scalability.

Provides senior-level technical leadership and hands-on development for network automation applications and infrastructure-as-code platforms. Builds full-stack services with Python, Java, JavaScript, Node.js, React, and Kubernetes; manages GitHub-based CI/CD; performs security and code reviews; and supports Dell SONiC, Cisco ACI, and Arista network environments. The role also develops observability, applies AI-assisted automation, troubleshoots infrastructure issues, participates in incident management, and mentors engineering teams.

Lead an agile team to design, build, deploy, and operate cloud-native data and ML platforms. Provide technical guidance, write and review secure production code, drive AI-assisted engineering adoption, migrate legacy big-data apps to cloud, build data pipelines and monitoring/provisioning tools, and influence architecture and automation across the SDLC.

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.

Leads cybersecurity architecture for software applications and platforms within wealth management. Drives secure product design, evaluates current and emerging technologies, establishes target architectures, and guides business and technical stakeholders. Oversees alignment with enterprise frameworks, regulatory requirements, scalability, resilience, and software development lifecycle practices. Serves as a subject matter expert in architecture governance and collaborates across teams to deliver secure, high-volume enterprise solutions.

Lead end-to-end analytics solutions to influence business strategy, mitigate risk, and optimize financial outcomes. Use data governance, predictive analytics, machine learning, ETL, and visualizations to derive insights, run experiments, and partner with stakeholders to improve collections, recoveries, and operational efficiency.

Review and audit machine learning models and model risk practices across the enterprise. Partner with cross-functional teams to design, train, evaluate, validate, and implement ML and NLP solutions, using tools like Python, Spark, H2O, and AWS. Translate technical findings into business recommendations and assurance for stakeholders and the Audit Committee, while researching and applying emerging Generative AI and state-of-the-art methods.

Supports AI, machine learning, and generative AI product initiatives for travel products. Responsibilities include identifying opportunities, developing requirements and user stories, coordinating cross-functional delivery, tracking projects with Agile tools, analyzing product metrics, conducting user and market research, and communicating AI-driven product impacts to stakeholders.

Lead control and risk management activities within Consumer & Community Banking. Partner with stakeholders to identify gaps, design and implement control strategies, use automation/AI/data analytics for monitoring, own Risk & Control Self-Assessments, drive regulatory compliance projects, and recommend improvements using digital risk management and agile practices.

Lead an agile engineering team to design, develop, test, and operate secure, scalable production software. Provide technical guidance, influence product and architecture decisions, deliver high-quality code, and promote firmwide engineering practices and modern cloud-native technologies.

Design and deliver secure software architecture, perform threat modeling and security risk analysis, implement and validate AI-assisted security workflows, produce architecture artifacts, identify gaps and mitigations, and collaborate with engineering teams to improve code quality and system resilience.

Design, build, and scale production-grade NLP and LLM-based solutions (search, summarization, classification, recommendations). Own end-to-end model lifecycle, partner with product/engineering/operations/risk, improve data quality and feedback loops, monitor models in production, and optimize workflows to reduce agent effort and improve consistency.

Lead cybersecurity architect responsible for designing and delivering cloud-native security solutions, threat modeling, secure design reviews, automation and CI/CD integration, vendor evaluations, AI-assisted security validation, driving reuse and controls compliance (e.g., NIST 800-53), and advising stakeholders while fostering communities of practice and inclusion.

Design and implement enterprise cybersecurity architecture for cloud-native applications. Embed security across SDLC and CI/CD, build Python automation for monitoring and remediation, evaluate vendors, lead practice communities, and collaborate with risk and compliance to translate regulatory requirements into technical controls while validating AI-assisted security outputs.

Build and validate ML, optimization, and statistical models on large structured and unstructured consumer datasets; generate insights and actionable recommendations; communicate results to senior stakeholders; contribute across the full modeling lifecycle and advance team knowledge.

Lead oversight of AI/ML and cybersecurity operational risk across the firm: evaluate technology and cyber practices, identify threats, challenge first-line mitigations, conduct thematic analyses, assess AI/ML use cases, and collaborate with stakeholders to strengthen controls and ensure responsible AI adoption.

Perform cyber threat intelligence and research, build automations and AI-assisted workflows, support incident response and remediation, assess supplier cyber posture, design AWS infrastructure, integrate data sources, and communicate risk and mitigation recommendations to stakeholders.

Lead cybersecurity architecture for cloud-native applications within consumer banking: define target state, assess risks, propose mitigations, drive automation, lead vendor evaluations and communities of practice, and communicate solutions to senior stakeholders.

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.

Nine-week summer analyst program within Operations supporting processing, trade/asset support, reporting, transformation, and data management. Responsibilities include transaction processing, reconciliations, client lifecycle support, data analytics and reporting, risk reporting, process improvement, and creating Tableau dashboards. Program includes training, networking, and may lead to full-time roles.

Lead data ownership and governance for wholesale credit risk. Define data strategies, ensure data quality, metadata and lineage, enable data products, mitigate data risks, and coordinate cross-functional delivery for analytics and reporting.

Ten-week, full-time paid Data Science internship (June–August 2027) working on machine learning, deep learning, and large-scale data analysis. Interns evaluate modeling tools, integrate internal and external data/APIs, design data science models, and present insights to stakeholders. In-person attendance at an assigned U.S. location is required; interns may be considered for full-time roles after graduation.