Machine Learning Jobs in Irving, TX

Data Engineering Interns will build and maintain scalable data pipelines, APIs, data products, and enterprise platforms. Responsibilities include data ingestion and transformation, software testing, CI/CD, cloud and distributed computing, data quality, governance, metadata, lineage, and reliability initiatives. Interns will also use approved AI tools, support AI-enabled engineering workflows, collaborate with technical and business teams, and participate in training, mentorship, and networking during the 10-week program.

Leads architecture, development, testing, validation, certification, and release of embedded software for robotic, autonomous, and safety-critical machines. Owns integration and build pipelines, develops operator and machine safety systems, evaluates AI and machine learning technologies, advises on complex integrations, and mentors engineers. The role requires extensive platform-level software development experience, robotics and autonomy expertise, an engineering or computer science degree, full-time onsite work in Irving, Texas, and up to 10% travel.

Leads execution and adoption of Real-Time Agent Assist capabilities, translating product direction into plans and measurable outcomes. Coordinates Product, Technology, Operations, Risk, Compliance, and Change Management stakeholders; manages dependencies and business readiness; evaluates AI use cases; defines requirements for performance, explainability, oversight, and responsible AI; and uses performance insights and user feedback to drive continuous improvement.

Develop autonomous and operator-assisted driving perception systems for off-road machines. Design, implement, optimize, and test sensor fusion, computer vision, object detection, tracking, and classification algorithms. Collaborate on machine learning data analysis, annotation, training, software integration, verification, validation, safety, and production deployment. Troubleshoot perception software using code, logs, sensor data, and machine performance information while participating in Agile development.

Lead robotics engineering efforts across perception, planning, control, and learning for autonomous off-road machines. Design, test, certify, and deploy production-quality autonomy components on real hardware, taking systems from prototype through production. Collaborate across the full robotics stack while specializing in AI, motion planning, perception, controls, or SLAM. Work includes simulation, vehicle deployment, field robotics, and potentially MLOps and training infrastructure.

Leads digital architecture for autonomous robotics and machine platforms. Defines technical standards, architecture patterns, and autonomy roadmaps spanning robotics, controls, machine integration, onboard computing, AI, and perception. Directs rapid prototyping, proof-of-concepts, architecture projects, and emerging technology evaluation while advising engineering teams and resolving complex technical issues. The role also establishes processes, influences stakeholders, and supports scalable deployment of safe, reliable autonomy capabilities across industrial machine platforms.

The Principal Robotics Engineer will design, develop, test, and deploy autonomy components across perception, planning, control, and learning for large off-road machines. The role owns robotics components from prototype through production on real hardware, contributes across the autonomy stack, and participates in software testing, analysis, witnessing, and certification. Responsibilities include field deployment, simulation, on-vehicle development, and collaboration within outcome-focused engineering teams.

Design, build, test, certify, and deploy autonomy components across perception, planning, control, and learning for large off-road machines. Own robotics components from prototype through production hardware, contribute across the autonomy stack, and support simulation, on-vehicle deployment, and real-world field operations.

Provides strategic cybersecurity architecture leadership across applications, data, networks, cloud, SaaS, and emerging AI technologies. Develops security requirements, designs secure technical architectures, assesses risk, improves security frameworks, supports SDLC activities, and supervises cybersecurity testing. Partners with business and executive stakeholders to enable strategic initiatives while strengthening security controls and resolving complex technical challenges.

Provides technical leadership and defines end-to-end architecture for Adobe Experience Cloud marketing technology and customer engagement solutions. Designs integrations, data flows, APIs, event-driven services, personalization, customer journey orchestration, and communication systems. Partners with product, engineering, security, compliance, marketing, and business teams to translate requirements into scalable, secure, resilient solutions. Supports architecture governance, prototyping, technical planning, risk management, and implementation-ready delivery in an agile environment.

Provides technical leadership for agile teams by defining end-to-end solution architecture and translating customer needs into technical designs. Designs Azure architectures for mobile and web applications, evaluates architectural alternatives, defines system components and interfaces, and develops architecture runway enablers through research and prototyping. Collaborates with product, application architecture, and engineering teams to create technical requirements, remove architectural impediments, and support program planning and solution demonstrations.

The Cybersecurity AI_ML Engineer develops and maintains security systems using AI and machine learning, implements threat detection, analyzes security metrics, and collaborates on security incidents.

Leads software engineering teams developing modern applications, platforms, and services. Provides architecture and coding expertise, manages budgets and resources, establishes technical learning plans, removes impediments, and improves delivery through metrics and testing. Partners with business operations, communicates strategies to executives, and oversees platform definition, software architecture, tool selection, automation, and regulatory alignment. The role requires 8–10 years of software development experience and expertise across cloud, integration, DevOps, programming, database, testing, and AI-enabled tools.

Design, develop, test, certify, and deploy autonomy components for large off-road machines across perception, planning, control, and learning. Take robotics solutions from prototype through production on real hardware, contribute across the autonomy stack, and collaborate in outcome-focused engineering pods. The role involves simulation, on-vehicle deployment, field robotics, and potentially machine-learning infrastructure.

Leads the creation and growth of Finance Insights & Decision Support for Pharmacy Services Finance. Establishes methodologies, investigates ambiguous business questions, applies analytics and AI-enabled techniques, translates findings into executive recommendations, and identifies opportunities to operationalize insights. Defines the function’s long-term vision, talent strategy, capability roadmap, and organizational structure while mentoring others and partnering with senior stakeholders.

Defines data architecture for physical AI and autonomous systems, including data contracts, schemas, metadata, governance, lineage, and traceability. Designs multimodal architectures for sensor, video, image, telemetry, event, simulation, and robotics data. Establishes scalable data patterns for robotics training, synthetic data, world models, and AI development. Leads architectural roadmaps and standards while partnering with simulation, robotics, data engineering, and platform teams.

Leads Vizient’s indirect spend data and analytics strategy, operating model, governance, quality standards, reporting, automation, and AI adoption. Oversees data lifecycle management, modeling, integration, categorization, normalization, analytical methodologies, dashboards, and decision-support tools. Manages data and analytics teams, develops reusable assets for consulting engagements, partners with technology and product teams, and supports business development and member presentations.

Designs and leads AI Quality Engineering for enterprise AI applications, LLMs, intelligent automation, and agentic systems. Responsibilities include building validation and testing frameworks, prompt and workflow testing, runtime quality controls, observability, telemetry, drift detection, reliability support, and release validation. The role collaborates across engineering, security, governance, clinical, data, and product teams to validate healthcare workflows and responsible AI deployments, while mentoring quality engineers and advancing AI-enabled testing practices.

Leads development of scalable full-stack applications using Java, Angular, microservices, and event-driven architectures. Integrates and deploys agentic AI, GenAI, and LLM-enabled systems for M&A use cases in a regulated enterprise environment. Responsibilities include architecture, coding, testing, CI/CD, security, operational support, environment readiness, risk management, mentoring, code reviews, and stakeholder collaboration.

Supports HR technology operations through Workday configuration, reporting, data management, integrations, security audits, troubleshooting, employee experience improvements, training, and system optimization. The role focuses on workforce management modules including HCM, Recruiting, Time Tracking, Absence, Scheduling, Compensation, and Reporting, while partnering with HR teams and business leaders to enhance processes, compliance, analytics, and system adoption.

Define and execute the product vision, strategy, roadmap, and priorities for web, mobile, and AI-enabled products. Lead initiatives from discovery through launch and continuous improvement while partnering with engineering, data science, design, security, and business teams. Monitor KPIs, user behavior, product analytics, and model performance to guide decisions. Ensure responsible AI practices addressing privacy, security, data quality, bias, and reliability.

Design, develop, test, and deliver scalable software applications, APIs, services, and user experiences. Build secure REST APIs, distributed services, event-driven integrations, and AI-enabled systems. Contribute to testing, CI/CD, observability, accessibility, security, performance, documentation, and technical design. Collaborate with product, architecture, data, quality, and business stakeholders while mentoring engineers and promoting consistent development practices.

Support analytical projects across Gartner's BTI and Product teams: analyze large datasets, build dashboards and reports, apply ML/AI and LLM tools, assist data pipeline setup, collaborate with data engineering and IT, and communicate insights to stakeholders. High-performing interns may receive full-time offers.

Entry-level Associate Data Analyst supporting analytics, data science, data engineering, and project management rotations. Deliver insights, build dashboards, automate reporting, partner with stakeholders, and apply ML/LLM tools to drive product and client analytics.

Design, develop, test, deploy, and support scalable software solutions, APIs, distributed services, user experiences, and AI-enabled systems. Collaborate with product, architecture, data, quality, and business stakeholders to deliver secure, incremental functionality. Contribute to testing, observability, accessibility, performance, CI/CD, technical documentation, code reviews, and continuous improvement while mentoring engineers and promoting strong engineering practices.