Quick overview
Job description
We are seeking for Staff AI Solutions Engineer to help deliver scalable AI/ML solutions across multiple business functions in onsemi. This role will be responsible for building AI/ML solutions and ensuring responsible AI governance in alignment with onsemi’s policies. You will report to the Sr. AI & Data Science Manager and collaborate to execute, mentor and accelerate AI/ML project delivery to drive business value.
We’re looking for a hands-on experienced engineer who can lead technical execution and mentor junior engineers. As a player-coach, you’ll be deeply involved in the technical details—guiding architectural decisions, ensuring AI safety, and shaping workflows using tools like LangGraph, Azure Machine Learning, Azure AI Foundry and MLflow. Your expertise in building scalable GenAI solutions and driving AI adoption will be instrumental n driving innovation.
- Assist decisions spanning the full AI/ML stack—from foundational infrastructure like model registries, CI/CD pipelines, and feature stores, to advanced orchestration and observability frameworks for LLMs using tools such as LangGraph, MLflow, Azure ML etc,
- Deliver data science project, from ideation to production, ensuring alignment with business goals and technical feasibility.
- Ensure compliance with onsemi’s Responsible AI Use and Governance Policies, including data privacy, model transparency, and ethical use.
- Partner with Infrastructure, Security, data engineering, and business teams to ensure end to end project delivery & execution.
- Build and optimize Retrieval-Augmented Generation (RAG) architectures leveraging enterprise knowledge sources, vector databases, and search technologies to improve response accuracy and relevance.
- Develop integrations with enterprise applications such as SAP, Salesforce, ServiceNow, SharePoint, Microsoft 365, and custom business systems through APIs and middleware platforms.
- Establish monitoring, evaluation, and observability frameworks to track model performance, response quality, hallucinations, latency, user adoption, and business value realization.
- Perform prompt engineering, workflow orchestration, model fine-tuning, and AI solution optimization to enhance effectiveness, user experience, and cost efficiency.
- Deploy AI solutions on Azure cloud and establish reusable design patterns.
Requirements:
- Master’s or PhD in Computer Science, Data Science, Statistics, or a related field.
- 7-10 years of experience in AI/data science.
- Proven experience deploying AI/ML solutions in production environments.
- Strong knowledge of cloud platforms (Azure preferred), MLOps, and data governance.
- Excellent communication and stakeholder management skills.
- Experience in semiconductor, manufacturing, or industrial domains is a plus.
Preferred Knowledge and Experience:
- Semiconductor industry experience.
- Experience with tools like LangGraph, Azure ML, and Snowflake.
- Understanding of AI security and compliance frameworks.
Competencies:
- Self-motivated, able to multitask, prioritize, and manage time efficiently
- Strong problem-solving skills
- Data analysis skills. Ability to analyze complex data and turn it into actionable information
- Collaboration and teamwork across multiple functions and stakeholders around the globe
- Flexibility and adaptability
- Drive for results, Able to work under pressure and meet deadlines
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