We are seeking a motivated recent graduate or AI/ML enthusiast to join our team and gain hands-on experience building intelligent document processing solutions. This paid internship provides exposure to cutting-edge AI technology, including Retrieval-Augmented Generation (RAG) systems and enterprise automation, within the dynamic telecommunications sector.

Why This Internship is Unique:

• Gain practical experience applying AI in enterprise settings, including telecoms, automation, and knowledge management.
• Develop foundational skills across data engineering, semantic search, and intelligent automation.
• Build a strong career foundation in AI/ML engineering, with potential for extended contracts or full-time roles at Anritsu.

Key Technical Responsibilities

As an intern, you will contribute to real enterprise AI projects while being guided and mentored by Anritsu engineers. Your responsibilities will include:

RAG System Architecture & Implementation

• Support the design and development of RAG pipelines using enterprise vector databases (e.g., Pinecone, Weaviate).
• Learn to process documents in multiple formats (PDF, Word, Excel, presentations) using OCR and content extraction.
• Assist in implementing semantic search strategies to improve accuracy and reduce errors.
• Contribute to integrating Large Language Models (LLMs) using frameworks such as LangChain and LlamaIndex.

Enterprise System Exposure

• Gain hands-on experience with MLOps pipelines for model deployment, monitoring, and iterative improvement.
• Learn how enterprises implement role-based access controls, audit trails, and governance frameworks.
• Support quality assurance frameworks to ensure compliance and error detection.

Advanced AI Engineering

• Explore multi-modal content parsing, including technical diagrams, tables, and structured datasets.
• Assist in prompt engineering and domain-specific fine-tuning.
• Learn to implement continuous learning systems with feedback loops and knowledge base enrichment.
• Exposure to cloud-native deployments using Docker, Kubernetes, and leading AI cloud services.

Required Qualifications

Educational Background:

• Bachelor’s degree in computer science, AI/ML, Data Science, Software Engineering, Mathematics, or a related field.
• Coursework or projects involving machine learning, AI, or data science (required).

Foundational Technical Skills:

• Curiosity about DevOps/MLOps practices (CI/CD pipelines, Docker, Kubernetes, model deployment).
• Exposure to deep learning frameworks (PyTorch, TensorFlow, or Hugging Face).
• Basic understanding of vector databases and semantic search (Pinecone, Weaviate, etc.).
• Experience with cloud platforms (AWS, Azure, GCP) through coursework or personal projects.
• Software development fundamentals: Git, APIs, and basic engineering practices.
• Conceptual understanding of transformer architectures, embedding models, and LLM fine-tuning.

Highly Preferred

• Interest in telecommunications or large enterprise systems.
• Passion for AI/ML and eagerness to learn and grow in this field.
• Strong problem-solving skills and willingness to tackle complex challenges.
• Team player, able to collaborate effectively in a fast-paced, supportive environment.
• Interest in enterprise security concepts: Role-based access control (RBAC), data governance, and compliance frameworks.

Bonus Skills & Achievements (Optional)

• Professional AI certifications (AWS Machine Learning, Azure AI Engineer, Google Cloud ML).
• Contributions to open-source AI/ML projects or publications in conferences/journals.

What You’ll Gain

By the end of this paid internship, you will have:

• Contributed to an end-to-end RAG system handling complex technical documents.
• Developed an understanding of enterprise knowledge base design and semantic search systems.
• Gained exposure to workflow automation and quality assurance frameworks in AI deployments.
• Enhanced your CV and portfolio with practical, hands-on AI/ML experience in a global telecom company.