Change the world. Love your job.
The Smart Manufacturing and Automation team at Texas Instruments develops analytics solutions to address challenges faced by manufacturing and engineering teams. As a global organization, we strive to create solutions that are compatible with all TI sites. We're looking for candidates to join our team in Richardson, TX as we leverage modern technologies to deliver data, analytics and AI solutions that enhance quality and productivity in semiconductor manufacturing.
About the job:
Texas Instruments is looking for a Sr. AI/ML engineer who is experienced with developing and deploying AI/ML solutions at scale. This role is critical to accelerating our digital transformation through rapid development of quality and test solutions using cutting-edge development techniques. The position offers the opportunity to revolutionize how our Smart Manufacturing and Automation team builds software while establishing best practices and scaling development capabilities across the organization.
We're seeking a Machine Learning Engineer with solid foundational expertise to develop and deploy intelligent solutions across our smart manufacturing platform. What sets this role apart: you'll leverage cutting-edge AI-assisted development platforms -Claude Code, GitHub Copilot, Cursor, and emerging agentic framework-to dramatically accelerate your development velocity while building production-grade ML systems. You'll collaborate with senior engineers and cross-functional teams to translate manufacturing challenges into scalable ML applications that directly impact manufacturing quality and test operations. This role emphasizes hands-on execution, rapid iteration, and learning: you'll build features that matter while growing your expertise in both ML engineering and AI-amplified development practices.
Key Responsibilities
Develop ML pipelines - implement end-to-end ML workflows combining structured and unstructured data; build data modeling for MFG data correlation inline and end of line data, feature engineering, training, and inference pipelines under technical guidance
Work with GenAI & LLMs - contribute to LLM-based features including RAG systems, prompt engineering, and agentic workflows; experiment with different approaches and document learnings
Collaborate on data architecture - work with data engineers to design and optimize data pipelines across our database systems; understand trade-offs between different storage architectures; integrate structured and unstructured data sources
Build and proto@type solutions - develop POCs for manufacturing problems; translate requirements into ML experiments; contribute to productionization of models with appropriate monitoring and testing
Deploy and monitor models - participate in end-to-end deployment; own model monitoring, retraining pipelines, and performance tracking; troubleshoot production issues with senior engineers
Write quality code - develop production-ready code with testing and documentation; follow Git workflows, JIRA tracking, and agile practices; participate in code reviews and learn from feedback
Why TI?
Engineer your future. We empower our employees to truly own their career and development. Come collaborate with some of the smartest people in the world to shape the future of electronics.
We're different by design. Diverse backgrounds and perspectives are what push innovation forward and what make TI stronger. We value each and every voice, and look forward to hearing yours. Meet the people of TI (https://edbz.fa.us2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX/pages/4012)
Benefits that benefit you. We offer competitive pay and benefits designed to help you and your family live your best life. Your well-being is important to us. Please find our country-specific benefits here (https://careers.ti.com/en/sites/CX/pages/benefits)
About Texas Instruments
Texas Instruments Incorporated (Nasdaq: TXN) is a global semiconductor company that designs, manufactures and sells analog and embedded processing chips for markets such as industrial, automotive, data center, personal electronics and communications equipment. At our core, we have a passion to create a better world by making electronics more affordable through semiconductors. This passion is alive today as each generation of innovation builds upon the last to make our technology more reliable, more affordable and lower power, making it possible for semiconductors to go into electronics everywhere. Learn more at TI.com .
Texas Instruments is an equal opportunity employer and supports a diverse, inclusive work environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, creed, disability, genetic information, national origin, gender, gender identity and expression, age, sexual orientation, marital status, veteran status, or any other characteristic protected by federal, state, or local laws.
If you are interested in this position, please apply to this requisition.
Minimum Requirements:
Bachelor's degree in Computer Science, Software Engineering, Computer Graphics Technology, Electrical Engineering, Computer Engineering or related field of study
5+ years of AI/ML experience - proven experience developing and deploying ML solutions with measurable impact
Computer Vision basics - working knowledge of image processing and computer vision techniques (classification, detection, or anomaly detection); experience with at least one CV framework
Generative AI exposure - hands-on experience with LLMs, prompt engineering, or RAG systems; familiarity with OpenAI, Anthropic, or similar APIs; curiosity about multi-agent systems
Database & data pipeline knowledge - working familiarity with relational and NoSQL databases; experience building or optimizing data pipelines; understanding of structured vs. unstructured data handling
Software engineering practices - proficiency with Git/GitHub, JIRA, issue tracking; ability to write clean, testable Python code; familiarity with agile development and CI/CD concepts
Preferred Requirements
Smart Manufacturing- prior work with IoT, manufacturing execution systems (MES), or connected factory environments
Advanced AI/ML capabilities - experience building with LLMs or generative AI APIs; familiar with prompt engineering and AI workflow optimization
Manufacturing or industrial domain exposure - familiarity with manufacturing environments, IoT systems, or operational processes; any exposure to semiconductor or discrete manufacturing
Production ML experience - experience deploying models to production; understanding of model versioning, monitoring, or retraining pipelines
DevOps & containerization - hands-on experience with Docker, Kubernetes, or cloud deployment (AWS, GCP, Azure); basic CI/CD pipeline knowledge
Multi-agent or advanced GenAI projects - exposure to agent frameworks, LangChain, or similar tools; experience with more complex LLM workflows beyond single-turn prompts
ECL/GTC Required: Yes
