Machine Learning Jobs in Plano, TX

Lead and scale teams to transform network infrastructure toward an Intent-Based, IaC-driven architecture. Drive automation, AI integration, microservices, cloud deployments, and engineering best practices while mentoring engineers, collaborating with product managers, and replacing manual ops with intelligent automation.

Lead and deliver large-scale technical programs and platforms, align cross-functional teams (product, engineering, design, data science), mitigate technical risk, drive execution and accountability, and deliver data-intensive and cloud-native solutions that meet business goals in a regulated environment.

Lead and grow multiple product-focused software engineering teams; mentor engineers; collaborate with product managers; improve engineering practices; design, develop, test, deploy and support full‑stack and microservice solutions on AWS; ensure availability, resilience, and scalability; migrate monoliths to microservices and drive adoption of modern technologies and Agile practices.

The Senior Lead Machine Learning Engineer will design, implement, and scale ML applications, ensuring performance and high availability while collaborating with cross-functional teams.

Lead feature delivery for AI/ML and search platforms powering virtual financial assistants. Provide technical direction, design and integrate AI/LLM models, ensure quality, mentor engineers, manage backlog and deploy/optimize AI workloads across CPU/GPU and cloud while enforcing security, observability, and responsible AI practices.

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.

Full‑stack software engineer responsible for designing, coding, unit/integration testing, and delivering scalable services for AI/search platforms. Work includes CI/CD, performance tuning, integrating components, contributing to test suites, performing spikes/proofs‑of‑concept, and collaborating in Agile teams to meet functional, non‑functional, and compliance requirements.

Executive leader responsible for driving value from MarTech, data, and AI to modernize P&C marketing. Owns audience strategy, lifecycle design, journey orchestration across channels (email, SMS, calls, onsite), testing and optimization, vendor/third-party risk, and capability roadmaps. Builds and leads teams, partners with centralized MarTech and stakeholders, briefs C-suite, and ensures compliance with regulatory and risk frameworks.

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 discovery, delivery, and performance of enterprise digital and technology products for omni-channel contact center solutions. Define product strategy, roadmaps, and business cases; drive cross-functional execution, measure KPIs/KRIs, mentor team members, and ensure risk/compliance alignment.

Assess AI/model governance and controls across the model lifecycle: review model development, validation, performance testing, assumptions, and monitoring; identify deficiencies; perform root cause analysis; collaborate with audit teams and stakeholders and communicate findings to management.

Lead systems engineering efforts including requirements engineering, systems integration, V&V, and MBSE. Drive technical planning, risk management, architecture/design development, lifecycle management, and mentor senior engineers to influence project direction and deliver ISR/aviation solutions.

The AI Engineer will prototype AI solutions, advise on integration, manage AI initiatives, and collaborate across technology teams, ensuring alignment with business needs. Roles include monitoring AI trends, engaging stakeholders, and conducting knowledge-sharing sessions on best practices.

Lead the global KCS Center of Excellence to align knowledge management with AI-driven support. Drive strategy, governance, team leadership, cross-functional integration, technology adoption (AI, ML, Salesforce, Splunk, Tableau), and change management to improve knowledge quality, findability, automation, CSAT, and cost-to-serve metrics.

Lead production of machine learning applications, provide technical expertise, and mentor engineers to drive ML model delivery at scale.

The Chief Data Officer will lead the enterprise-wide data strategy, ensuring data quality and governance while driving AI initiatives and business value.

The Lead Data Science Product Manager will lead AI initiatives, engage with executives, design AI solutions, and provide overall product leadership.

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.

Lead AI/ML-focused information security for enterprise agentic capabilities. Advise projects and CSOC teams on threat mitigation, compliance, automation, monitoring, and incident response. Partner with engineering and stakeholders to secure cloud, generative AI, and customer servicing platforms while driving data-driven decisions and continuous improvements.

The Senior Product Manager will lead mainframe foundational products, collaborating with teams to develop the product vision, roadmap, and feature prioritization, while ensuring customer adoption and satisfaction.

The Senior Product Owner leads product development for Mainframe solutions at Broadcom, collaborating with cross-functional teams to deliver features based on customer needs and product roadmaps.

Design, develop, test, deploy, maintain, and enhance large-scale software solutions. Provide technical leadership and manage project priorities. Fine-tune foundation models and build adapters (Llama Factory, PEFT). Apply RAG techniques to populate and query vector databases (Weaviate). Build custom applications using LLM frameworks such as LangChain and DSPy.

Design, develop, and deploy scalable machine learning models and data pipelines for production. Collaborate with data scientists, engineers, and stakeholders, optimize model performance and scalability, automate deployments, monitor production systems, and evaluate emerging ML and cloud technologies to drive business outcomes.

Deploy, maintain, and improve production ML workflows and platforms for media measurement and customer analytics on AWS. Build SageMaker jobs and endpoints, orchestrate pipelines with Step Functions, Lambda, and Airflow, manage model artifacts and CI/CD, troubleshoot production issues, and collaborate on platform enhancements and operational best practices.

Early-career role to characterize AI/ML workloads, build performance and hardware-mapping models, identify compute/memory/power bottlenecks, collaborate with SoC/IP and compiler teams, and communicate results via reports and design reviews.