Machine Learning Jobs in Richardson, TX

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.

Owns the roadmap, strategy, risk management, and continuous improvement of data platforms supporting financial-crime analytics, detection models, investigations, and AML operations. Responsibilities include requirements gathering, backlog prioritization, agile delivery, data analysis, model lifecycle management, monitoring, issue remediation, governance, and stakeholder communication across business and technology teams.

Leads systems engineering for next-generation airborne command and control aircraft. Responsibilities include requirements engineering, systems integration, verification and validation, MBSE, architecture development, technical planning, risk management, lifecycle management, and decision analysis. The role influences project direction, mentors senior engineers, manages critical components, and supports aerospace systems certification and testing. It requires extensive leadership, multidisciplinary development experience, and active Secret clearance.

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.

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.

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.

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.

Leads global product process excellence and business transformation initiatives, converting drawing-based product knowledge into structured, governed digital definitions. Oversees product configuration, engineering platforms, PLM and ERP integrations, digital thread strategy, process standards, AI adoption, and organizational change. Partners across product development, manufacturing, IT, business transformation, and regional teams to improve data quality, traceability, configuration accuracy, order handoff, and manufacturing readiness.

Drive fraud strategy, policy, and analytics for money-movement fraud. Build and manage fraud rules, analyze moderately complex data sets using SQL/Python/SAS and BI tools, create predictive models and visualizations, consult stakeholders, and ensure fraud risk is identified and controlled across payment channels.

Lead product management for enterprise product and experience initiatives, partnering with design, data, ML, and engineering to define strategy, prioritize roadmap, prototype solutions, and deliver customer-centric, technology-driven products that achieve business outcomes.

Lead enterprise product and experience initiatives, guiding cross-functional teams (product, data, design, ML, engineering) to define strategy, deliver customer-centric digital products, prototype and apply emerging AI/automation tools, and drive transformational outcomes across Capital One.

Develop and support scalable software and AI-powered applications for Bank of America’s conversational AI, search, and virtual assistant platforms. Responsibilities include designing architecture, coding, testing, building RESTful APIs and microservices, implementing Generative AI and RAG solutions, automating CI/CD and releases, troubleshooting production issues, and supporting deployment and monitoring. The engineer will collaborate in Agile teams, contribute to technical decisions, conduct code reviews, and mentor other engineers.

Supports business decision-making through data analysis, predictive modeling, statistical and machine learning techniques, and presentation of insights. Interns will work across marketing, lending, indirect lending, and warranties while gaining hands-on experience throughout the data science lifecycle. The role is an 11-week, paid, on-site internship based in Tempe, Arizona, or Dallas, Texas, with no relocation assistance.

Leads the Underwriting Data Engineering team and oversees the design, development, and productionization of scalable data and machine learning pipelines. Responsibilities include feature engineering, data preparation, model deployment, data validation, governance, monitoring, API integration, analytic data products, roadmap development, stakeholder collaboration, and team coaching.

Lead and deliver advanced analytics and machine learning solutions to support pricing, revenue optimization, and partner relationships. Collaborate with cross-functional teams to design, validate, and implement models at scale using large transaction datasets and modern big-data tooling. Translate technical insights into actionable business recommendations.

Build and integrate enterprise AI solutions using pre-trained LLMs, RAG architectures, traditional machine learning, AI agents, and deterministic logic. Develop backend APIs, React interfaces, data pipelines, and integrations with ServiceNow, SAP, Salesforce, and Azure. Support testing, deployment, monitoring, documentation, and workflow orchestration using LangChain and n8n while collaborating with AI, data, and platform teams.

Build and integrate enterprise AI solutions using pre-trained LLMs, RAG architectures, traditional machine learning, AI agents, and deterministic logic. Develop backend APIs, React interfaces, data pipelines, and integrations with ServiceNow, SAP, Salesforce, and Azure. Support testing, deployment, monitoring, documentation, and workflow orchestration using LangChain and n8n. Collaborate with AI, data, and platform teams on production-ready solutions while developing applied Generative AI engineering skills.

Develop, validate, maintain, and monitor machine learning models and data pipelines. Analyze forecasting, experimentation, and statistical problems, document model assumptions and limitations, and explain results to non-technical stakeholders. The role involves cloud data platforms, productionizing models, and contributing to model validation and monitoring standards while partnering with data science, analytics, and business teams.

Leads strategic account management for self-insured employer clients using healthcare data analytics. Responsibilities include managing client relationships, coordinating implementations and internal resources, translating claims and analytical insights into actionable recommendations, delivering presentations and reports, troubleshooting issues, monitoring KPIs, and identifying growth opportunities. The role also supports contract negotiations, healthcare payment integrity initiatives, and collaboration with data science, clinical, sales, and executive teams.

Lead RTL development and microarchitecture for an AI-enabled RISC-V CPU core, including vector and matrix engines. Own functional features, performance, power, area, timing, and physical design considerations. Develop specifications, optimize RTL, support verification, and collaborate on CPU modeling, design verification, and SoC integration. The role requires deep expertise in high-performance CPU architecture, cache and memory subsystems, SystemVerilog or related HDL technologies, and advanced processor design.

The CTO will lead technology modernization efforts, drive innovation in cloud computing and analytics, and oversee the transformation of core insurance platforms to enhance customer experiences and business growth.

Design, develop, test, and integrate geospatial software capabilities across the full SDLC. Collaborate in Agile teams, integrate cross-system capabilities, perform prototyping, contribute documentation, and support deployment and maintenance while applying GEOINT/SIGINT/IMINT domain knowledge.

Supports drilling, completions, and production engineers in 24/7 rotational operations. Responsibilities include geo-steering horizontal wells, monitoring drilling performance, troubleshooting operational issues, conducting offset and performance analysis, developing technical studies, supporting well planning and regulatory processes, performing directional and anti-collision planning, and providing torque and drag recommendations. The role also uses multiple operational data platforms and requires field visits and night-shift availability.

Administer and continuously improve the OneStream finance platform: design dimensional and cube architecture, manage business rules, integrations, security, release promotion, and production support. Partner with Finance, Accounting, IT, and external consultants to support consolidation, forecasting, reporting, SOX controls, training, and process improvement across development, test, and production environments.

Lead design and productionization of advanced ML systems (NLP, speech, recommendations, IR, and agentic/Generative AI). Build and fine-tune LLM/SLM solutions (RAG, tool-calling agents), apply RL/RLHF and PEFT techniques, ensure scalable, secure, and measurable deployments, and collaborate cross-functionally to drive product impact.