Machine Learning Jobs in Plano, TX

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.

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.

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.

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.

Lead end-to-end development and production deployment of causal and predictive ML solutions for private banking. Frame causal problems, build uplift/HTE models and observational causal studies, drive MLOps, monitor model quality, mentor data scientists, and translate causal/LLM research into production in partnership with risk, compliance, and business stakeholders.

The Business Development Specialist will identify sales opportunities, conduct market research, develop business strategies, and build customer relationships to achieve sales targets in data and AI solutions.

Lead systems engineering for ISR/aviation programs, owning requirements engineering, MBSE, systems integration, V&V, architecture, technical planning, risk management, lifecycle activities, and mentoring senior engineers to deliver mission systems.

Lead production-focused AI and machine learning development across classification, prediction, generative AI, LLM, and agentic use cases. Own modeling, evaluation, deployment, monitoring, and lifecycle improvement for customer-facing capabilities. Partner with Product, Engineering, Data Engineering, and MLOps to assess feasibility, prioritize opportunities, establish evaluation standards, and translate complex automotive data into reliable, scalable AI products. The role also provides technical leadership and product judgment without direct people-management responsibility.

Develop reusable ML tooling and libraries, collaborate with data scientists to productionize models, build services and APIs (Docker/Linux), follow engineering best practices, and support project lifecycle from intake to maintenance.

Lead a forward‑deployed AI solutions team to translate enterprise AI capabilities into business outcomes. Partner with executives to co‑design and deliver priority use cases, drive AI productivity tool adoption, establish repeatable AI solution patterns, and feed learnings back into the AI platform and governance. Balance rapid delivery with enterprise rigor while coaching teams and managing stakeholders.

Design and implement full-stack Java solutions; define business processes and architecture; work with cloud platforms (AWS/Azure/VMware), infrastructure orchestration, scripting, configuration management, and big-data technologies; apply machine learning libraries; operate in a consulting environment with regular travel.

Design, develop, and deploy production-grade full-stack AI applications and agentic AI solutions. Build AI agents, multi-agent workflows, RAG pipelines, LLM applications, conversational interfaces, and scalable microservices using Java or Python and AWS services. Implement prompt engineering, evaluation, observability, guardrails, CI/CD, containerization, APIs, and infrastructure as code. Troubleshoot and optimize production systems in enterprise environments.

Lead workload-driven AI/ML systems architecture across hardware and software. Own workload characterization, analytical performance modeling, KPI definition, and hardware performance analysis to guide SoC, memory, and HW/SW co-design decisions. Evaluate compute, memory, latency, and software bottlenecks; collaborate with CPU, compiler, runtime, and ML framework teams; present recommendations to leadership; and mentor junior engineers. The role requires expertise in processor and memory architecture, edge AI acceleration, performance modeling, and cross-functional technical leadership.

Lead RTL development and microarchitecture for an AI-enabled RISC-V CPU core. Responsibilities include designing vector and matrix-processing engines, optimizing power, performance, area, and timing, developing detailed specifications, supporting functional verification, debugging simulations, and partnering on physical design validation. The role requires expertise in high-performance processor architecture, datapath design, vector and matrix processing, and hardware design languages.

Summer data science internship working on ML projects (anomaly detection, numerical optimization, PII/PHI NLP). Interns will develop models, write high-quality Python, use Linux and development tools, work with git, Docker, CI/CD and Kubernetes, participate in code reviews and agile rituals, and present results to technical and non-technical audiences.

Develop and productionize AI features from PoC to scalable deployments. Write production-ready Python code, implement testing and debugging, refine user stories, participate in ethical and security reviews, and collaborate with stakeholders to align AI solutions with business needs.