Please note this posting is to advertise potential job opportunities. This exact role may not be open today but could open in the near future. When you apply, a Cisco representative may contact you directly if a relevant position opens.

Application Deadline: March 31 2026

Location: PRG5 office

Hybrid

20 hours per week

Who You’ll Work With

We are a bunch of former security startups collectively called Threat Detection and Response. We keep an agile, fun, and passionate upstart culture within Cisco. You will work in an international environment in downtown Prague, Czech Republic, closely cooperating with teams in the US. We balance collaboration and integration with autonomy and innovation to deliver the most effective solution to our customers’ problems. The unique mix of our disruptive approach to security and Cisco’s industry dominance surpasses what any other security startup could ever achieve on its own.

Your Impact

We are seeking a motivated Machine Learning Researcher or Machine Learning Engineer Intern to join our team. The ideal candidate will have a solid foundation in machine learning concepts and a passion for applying their skills to real-world problems. This internship offers a unique opportunity to gain hands-on experience, contribute to exciting projects, and work alongside experienced researchers and engineers.

Possible Projects you could work on:

Identifying Threats in E-mail Cybersecurity Data – E-mail has been one of the primary attack vectors for years, both within personal and business field. Identifying phishing and other malicious abuse within e-mail communication is thus of big interest. Now, with the surge of LLMs, the threat detection is even more challenging as the attackers are using all the available tools to pretend their e-mails being as legitimate as possible. We are looking for interns that would participate in our threat detection ML research and ML Engineering – within text processing and LLMs, structured data processing, data science work and more traditional ML research, and the results should end up in our E-mail threat detection product.

One possible, more specific, topic might be exploration of deeper structural cues hidden in modern HTML-based e‑mails. By modelling the HTML structure, for example as a graph, we can capture patterns that help reveal sophisticated or obfuscated malicious behavior. Further internship topics might cover other types of additional context for the detection system that would serve for identifying new deceptive techniques.

Incident Similarity – the breach protection systems generate a wide variety of detection events, which are aggregated into incidents. These incidents, containing diverse information ranging from textual descriptions to numerical data, are then managed by security operations teams to safeguard organizational assets. This example project focuses on researching similarity measures that can identify incidents with similar information, meaning, and impact on the system, thereby enhancing incident correlation and response effectiveness.

LLM Features Enhancement – the goal is to advance the capabilities of large language models (LLMs) used in incident summarization and contextualization within security operations. This work involves tasks such as prompt engineering to design effective instructions that guide the LLMs, evaluating model performance, measuring output quality, and developing features that generate inputs for prompts. The goal is to improve how incidents are summarized and understood by leveraging LLMs, thereby enhancing the accuracy and relevance of contextual information provided to security teams. This project represents the kind of innovative AI-driven work that supports automated, intelligent incident analysis and decision-making processes.

What you will do

• Assist in inventing, designing, developing, and evaluating innovative models on large-scale data.

  • Support the design and implementation of scalable, efficient, automated Machine Learning pipelines.

  • Contribute to innovation projects from idea to implementation under guidance.

• Collaborate closely with teams of software, AI and ML engineers

• Be eager to learn about cybersecurity data analytics and related tools.

• Help communicate results through internal reports, blogs, and assist in preparing for scientific papers and conference presentations.

Minimum Requirements:

• Currently pursuing a degree in Computer Science, Data Science, Machine learning, or a related field

• Proficient in English

Preferred Requirements:

• Basic understanding or coursework in software engineering is a plus.

• Experience with coursework in one or more of the following Machine Learning fields: supervised, semi-supervised, or unsupervised learning, explainability of models, advanced statistics, graph theory, game theory.

• Strong logical reasoning and problem-solving skills.

• Enthusiasm for completing tasks and making projects successful.

• Hands on experience with any of the technologies such as scikit-learn, Pandas, PyTorch, LLMs, text embeddings, (py)Spark will boost the start

Why Cisco?

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

We are Cisco, and our power starts with you.