Software Engineer

Intel Intel · Semiconductors · Arizona, Phoenix, United States +1

Software Engineer role focused on applying AI/ML to develop and enhance software tools for advanced packaging and silicon enablement. The role involves building intelligent features, optimizing workflows, and integrating AI/ML across the full software development lifecycle, with a focus on shipping AI-enabled products.

What you'd actually do

  1. Design, develop, and enhance software tools and automation solutions that support engineering workflows in advanced packaging and silicon enablement.
  2. Apply AI/ML techniques end-to-end to improve tool capability, automation, decision support, and workflow efficiency.
  3. Build and integrate intelligent features into software systems, including data-driven automation, predictive capabilities, and workflow optimization.
  4. Collaborate closely with engineering, research, and product teams to understand requirements and translate them into scalable technical solutions.
  5. Contribute to the architecture, design, implementation, testing, and deployment of AI/ML-enabled software tools.

Skills

Required

  • 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
  • Strong programming skills in one of the following: (C++ (preferred), Python, C# with solid foundations in data structures, algorithms, and software engineering principles)

Nice to have

  • 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, TensorFlow, 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 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, version control, testing, CI/CD, and cloud-native development practices

What the JD emphasized

  • Ability to obtain a US Government TS/SCI Security Clearance with Polygraph
  • 1+ years of experience designing, deploying, and maintaining scalable, reliable AI/ML production systems
  • End-to-end experience with generative AI and LLM-based solutions

Other signals

  • apply AI/ML techniques end-to-end
  • build and integrate intelligent features
  • evaluate new AI/ML technologies
  • end-to-end experience with generative AI and LLM-based solutions