Cisco Machine Learning Engineer Intern Hyderabad 2026 – Exciting GenAI Internship, Apply Online Now

Cisco Machine Learning Engineer Intern Hyderabad opening under the Cisco Splunk / UHR India Engineering division is one of the most exciting AI internship opportunities of 2026 for Master’s students graduating in 2027. Cisco is hiring a Machine Learning Engineer Master’s Intern at its Hyderabad center to design, train, and optimize Large Language Models (LLMs), multimodal AI systems, and generative AI solutions that directly power Cisco’s next-generation collaboration, networking, and observability products. If you have hands-on experience in deep learning frameworks, NLP, computer vision, and GenAI model fine-tuning, this high-impact internship at one of the world’s leading technology companies is your gateway to doing career-defining AI work in 2026.

Job Details

About The Company

Cisco Systems is the world’s leading networking, cybersecurity, and collaboration technology company, founded in 1984 and headquartered in San Jose, California, USA, with a massive engineering presence in Hyderabad and Bangalore, India. Cisco’s acquisition of Splunk in 2024 created one of the most powerful AI-driven observability and security platforms in the world, making Cisco’s India engineering teams central to some of the most ambitious AI and ML initiatives globally. At Cisco, AI is not just a technology — it is a movement, with teams working at the intersection of deep learning, generative AI, and large-scale product design to create meaningful impact for billions of users worldwide.

Eligibility Criteria

Education: Currently pursuing a Master’s degree (M.Tech / MS / MBA-Tech) in Computer Science, AI, Machine Learning, Data Science, or related fields

Experience: Students graduating in 2027 are eligible

Technical Skills:

• Programming experience in Java, C++, Python, or related languages
• Hands-on experience in Natural Language Processing (NLP), Computer Vision, or multimodal interaction systems
• Experience using deep learning frameworks (PyTorch, TensorFlow, JAX) to train, fine-tune, and optimize GenAI models for performance and scalability
• Experience designing and deploying proof-of-concepts and production-ready AI systems

Preferred / Good-to-Have Skills:

• Strong background in system design, software development, and production deployment at scale
• Ability to transform ambiguous requirements into actionable deep learning solutions
• Familiarity with state-of-the-art GenAI models and methods — CLIP, DALL-E 2, Diffusion Models, GPT-family LLMs, BERT, T5
• Demonstrated contributions to the AI/ML community — top-tier publications (NeurIPS, ICML, ACL, CVPR), open-source projects, or Kaggle/leaderboard competitions

Roles & Responsibilities

• Design, train, and optimize Large Language Models (LLMs) and multimodal AI systems to address real-world challenges across Cisco’s product portfolio
• Drive innovation by developing scalable, high-performing GenAI solutions for collaboration, networking, security, and observability products
• Collaborate with engineering and product teams across Cisco and Splunk to integrate AI capabilities into production systems
• Guide and contribute to research into emerging AI technologies — diffusion models, multimodal transformers, retrieval-augmented generation (RAG), and agentic AI
• Deploy proof-of-concept and production-ready AI systems with a focus on scalability, latency, and performance optimization
• Contribute to Cisco’s generative AI strategy by developing impactful AI capabilities that transform customer experiences
• Mentor peers and evangelize AI innovation both within Cisco and in the broader AI/ML community
• Document research findings, model performance benchmarks, and deployment architectures for internal knowledge sharing

Selection Process

1. Online Application Submission – Resume shortlisting based on ML/AI experience, research contributions, and academic background
2. HR Screening Call – Communication, role fitment, and graduation timeline validation
3. Technical Assessment – ML fundamentals, Python coding, deep learning concepts, and model design problem-solving
4. Technical Interview Round 1 – NLP/CV/multimodal AI concepts, deep learning framework hands-on, LLM fine-tuning methodology
5. Technical Interview Round 2 – System design for AI at scale, production deployment challenges, GenAI architecture discussion
6. Hiring Manager Round – Research mindset, innovation approach, collaboration skills, and project fitment
7. Offer & Onboarding – Internship offer with details on duration, stipend, and mentorship structure

How to Apply For Cisco Machine Learning Engineer Intern Hyderabad

1. Visit the official Cisco Careers portal: Link Given Below
2. Click “Apply Now” and log in or create your Cisco careers account
3. Upload your updated resume highlighting deep learning projects, NLP/CV experience, GenAI model work, publications, and open-source contributions
4. Complete the application form and submit
5. Monitor your registered email for Cisco recruiter communication — note this is a pipeline posting and a Cisco representative will contact you when a relevant position opens

Preparation Tips

• Master PyTorch for LLM work — practice transformer architecture from scratch, attention mechanisms, positional encoding, and fine-tuning pre-trained models (BERT, GPT-2, LLaMA) using HuggingFace Transformers library
• Get hands-on with LLM fine-tuning techniques — study Parameter-Efficient Fine-Tuning (PEFT) methods: LoRA, QLoRA, Prefix Tuning, and Prompt Tuning for adapting large models to downstream tasks efficiently
• Study multimodal AI architectures — understand CLIP (contrastive vision-language pretraining), DALL-E, Stable Diffusion, and Flamingo to prepare for discussions on state-of-the-art GenAI models
• Build a strong ML system design foundation — practice designing end-to-end ML pipelines: data ingestion → feature engineering → model training → evaluation → serving → monitoring at production scale
• Contribute to open-source AI projects — HuggingFace model contributions, Kaggle competition top rankings, or GitHub ML repositories significantly strengthen your Cisco ML intern application
• Publish or prepare research work — even workshop papers, arxiv preprints, or strong project reports from M.Tech courses demonstrate research capability valued highly at Cisco’s AI teams
• Study Retrieval-Augmented Generation (RAG) — RAG architectures combining LLMs with vector databases (Pinecone, FAISS, Weaviate) are actively used in Cisco’s observability and security AI products
• Practice Python coding for ML interviews — LeetCode Medium/Hard problems on arrays, graphs, and dynamic programming combined with ML-specific coding questions (implement backpropagation, write a transformer attention layer from scratch) are commonly tested

Important Dates

⚠️ Important Note: This is a pipeline/future opening posting. Cisco representatives will contact shortlisted candidates directly when a relevant position formally opens. Apply early to ensure your profile is in the pipeline.