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Senior Applied AI Engineer
לא צויןמשרה מלאהAI EngineeringElectronics Manufacturing
Develop and operate production AI solutions that unify engineering data, enable advanced analytics, and improve productivity across ASIC networking product engineering workflows.
תחומי אחריות
- Design, build, and maintain AI solutions for production, characterization, analysis, and operational workflows.
- Develop AI agents and copilots that allow engineers to query, analyze, and reason over ASIC data.
- Consolidate data from infrastructure and engineering systems into scalable pipelines and reusable services.
- Partner with production engineering teams to identify use cases and deliver measurable improvements.
- Build tools for data access, automation, reporting, anomaly detection, and engineering insight generation.
- Collaborate across teams to improve interfaces and data quality and support scalable deployment.
- Use feedback, monitoring, and roadmap planning to drive continuous improvement.
דרישות
- Bachelor’s degree in computer science, software engineering, data science, or a related field, or equivalent experience.
- At least 8 years of experience as an AI solutions engineer, machine learning engineer, or software engineer building production AI or data solutions.
- Strong experience designing, developing, deploying, and maintaining end-to-end production AI applications.
- Hands-on expertise with Python and modern software engineering practices.
- Practical experience with large language models, AI agents, retrieval-augmented generation, workflow orchestration, and data analytics applications.
- Strong experience building data pipelines, APIs, services, and applications using structured and semi-structured engineering data.
יתרון
- Experience supporting AI solutions for engineering or manufacturing organizations.
- Familiarity with agent frameworks, vector databases, telemetry platforms, or internal knowledge and data systems.
- Experience spanning software, data, infrastructure, and product engineering.
- Experience introducing technical capabilities and driving adoption across engineering teams.
- Background in semiconductor, hardware, product engineering, testing, characterization, or manufacturing analytics.