AI/ML Engineer
Role details
Job location
Tech stack
Job description
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., + 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
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Work with GenAI & LLMs - contribute to LLM-based features including RAG systems, prompt engineering, and agentic workflows; experiment with different approaches and document learnings
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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
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Build and prototype solutions - develop POCs for manufacturing problems; translate requirements into ML experiments; contribute to productionization of models with appropriate monitoring and testing
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Deploy and monitor models - participate in end-to-end deployment; own model monitoring, retraining pipelines, and performance tracking; troubleshoot production issues with senior engineers
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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?
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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.
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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)
Requirements
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Bachelor's degree in Computer Science, Software Engineering, Computer Graphics Technology, Electrical Engineering, Computer Engineering or related field of study
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5+ years of AI/ML experience - proven experience developing and deploying ML solutions with measurable impact
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Computer Vision basics - working knowledge of image processing and computer vision techniques (classification, detection, or anomaly detection); experience with at least one CV framework
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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
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Database & data pipeline knowledge - working familiarity with relational and NoSQL databases; experience building or optimizing data pipelines; understanding of structured vs. unstructured data handling
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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
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Smart Manufacturing- prior work with IoT, manufacturing execution systems (MES), or connected factory environments
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Advanced AI/ML capabilities - experience building with LLMs or generative AI APIs; familiar with prompt engineering and AI workflow optimization
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Manufacturing or industrial domain exposure - familiarity with manufacturing environments, IoT systems, or operational processes; any exposure to semiconductor or discrete manufacturing
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Production ML experience - experience deploying models to production; understanding of model versioning, monitoring, or retraining pipelines
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DevOps & containerization - hands-on experience with Docker, Kubernetes, or cloud deployment (AWS, GCP, Azure); basic CI/CD pipeline knowledge
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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
Benefits & conditions
- 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)