Software Engineer, AI Engineer (Applied​/Software), Machine Learning​/ ML Engineer

Job Details Job Description Who We Are

Advanced Packaging and Technology Manufacturing Group, we develop 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.

• 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.

• Work effectively in a fast-paced, research-driven environment with evolving requirements.
• Problem-solving, analytical thinking, and communication skills.
• Work independently as well as collaboratively within a multidisciplinary team.
• Ability to collaborate cross-functionally, contribute to technical design discussions, and deliver high‑quality, maintainable software solutions.

Minimum Qualifications:

• U.S. Citizenship required.
• Ability to obtain a US Government TS/SCI Security Clearance with Polygraph.
• Bachelor's degree in computer science, Computer Engineering/Artificial Intelligence, Machine Learning or in a related field.
• 1+ years of experience designing, deploying, and maintaining scalable, reliable AI/ML production systems.
• 1+ years of experience with Strong programming skills in one of the following: (C++ (preferred), Python, C# with solid foundations in data structures, algorithms, and software engineering principles).

Preferred Qualifications:

• Maters in Computer Science, Computer Engineering/Artificial Intelligence, Machine Learning or in a related field.
• Experience with EDA tools.
• End-to-end experience with generative AI and LLM-based solutions, including one or more of the following: prompt engineering, embeddings, vector databases, semantic search, and RAG workflows.
• 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, Tensor Flow, or Scikit-learn.
• Experience deploying AI/ML services using Docker, Kubernetes, cloud platforms, REST/gRPC APIs, or serverless architectures.
• Strong understanding of system design, distributed computing, performance…