Software Engineer

Intel•Chandler, AZ

2d•Onsite

About The Position

At Advanced Packaging and Technology Manufacturing Group, we build software tools and technologies that help shape the future of foundry and Intel products. Our work in advanced packaging and silicon enablement supports engineering teams in staying at the forefront of cutting-edge semiconductor technologies. We operate in a fast-paced, research-driven environment where innovation, collaboration, and technical excellence are critical to success. In this role, we are looking for a strong team player who can help redefine and shape the next generation of software automation and engineering tools through the end-to-end infusion of AI/ML technologies. The ideal candidate will contribute to building intelligent, scalable, and efficient software solutions that accelerate engineering workflows, improve productivity, and support innovation across advanced packaging and silicon development initiatives. This role requires someone who is comfortable working in a dynamic environment, partnering with technical teams, and applying AI/ML across the full software development lifecycle.

Requirements

Master’s degree in AI/ML, Data Science/ Computer science, Software Engineering, Electrical Engineering.
6 months of experience in: Software development skills with experience in building engineering applications, automation tools, or enterprise software solutions.
Hands-on experience with AI/ML technologies and their practical application in software systems.
Programming languages such as Python, C++, Java, or similar.
Software design, development, testing, and debugging in a collaborative environment.

Nice To Haves

Hands on experience designing, deploying, and maintaining scalable, reliable AI/ML production systems.
End-to-end experience with generative AI and LLM-based solutions, including prompt engineering, embeddings, vector databases, semantic search, and RAG workflows.
Foundations in data structures, algorithms, and software engineering principles.
Hands-on experience building scalable applications, backend services, APIs, or distributed systems, including integration of ML models into software.
Experience with machine learning systems, including model training, evaluation, inference, and use of frameworks such as PyTorch, TensorFlow, or Scikit-learn.
Experience deploying AI/ML services using Docker, Kubernetes, cloud platforms, REST/gRPC APIs, or serverless architectures.
Familiarity with MLOps/LLMOps practices, including model versioning, experiment tracking, monitoring, and performance evaluation.
Understanding of system design, distributed computing, performance optimization, security, privacy, and responsible AI principles.
Experience working with large-scale datasets, data pipelines, or big data/streaming technologies such as Spark, Databricks, or Kafka.
Familiarity with databases (SQL/NoSQL), version control, testing, CI/CD, and cloud-native development practices.

Responsibilities

Design, develop, and enhance software tools and automation solutions that support engineering workflows in advanced packaging and silicon enablement.
Apply AI/ML techniques end-to-end to improve tool capability, automation, decision support, and workflow efficiency.
Build and integrate intelligent features into software systems, including data-driven automation, predictive capabilities, and workflow optimization.
Collaborate closely with engineering, research, and product teams to understand requirements and translate them into scalable technical solutions.
Contribute to the architecture, design, implementation, testing, and deployment of AI/ML-enabled software tools.
Develop robust, maintainable, and production-quality code in a fast-paced development environment.
Evaluate new AI/ML technologies, frameworks, and approaches to drive innovation in engineering productivity and automation.
Support experimentation, prototyping, and iterative refinement of new solutions in a research-focused setting.
Ensure software solutions are reliable, scalable, and aligned with engineering and business goals.
Participate in code reviews, design discussions, and cross-functional technical problem-solving.