Machine Learning Researcher Intern - Prague
Cisco Systems
Application Deadline: 2025-04-30 Location: PRG5 office Hybrid 20 hour per week
Who You’ll Work With
We are a bunch of a former security startups collectively called Threat Detection and Response. We keep an agile, fun, 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.
Who You Are
We are seeking a motivated Machine Learning Researcher 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:
Similarity Search on Sequence of Endpoint Security Events – Each monitored device in a computer network outputs streams of cybersecurity events. This project focuses on finding common patterns in these streams to identify similarly behaving devices using similarity search techniques. The data stream is segmented into sequences of related events, which are then represented in an embedding space to identify similar sequences.
Advance Command Line Preprocessing – Building a robust system to correlate individual cybersecurity events into incidents requires understanding the activity on impacted devices rather than just matching parameters. This project focuses on understanding and normalizing command lines leading to cybersecurity events. Command lines often contain specific parameters like usernames, hashes, or random strings that obscure their functionality. Removing or masking these values can help uncover similar patterns across different devices or environments, providing robust similarity measures between cybersecurity events.
Learning on Cybersecurity Relational Data – Cybersecurity investigations often rely on relationships between entities like IP addresses, URLs, email addresses, documents, binaries, and internet users. This project examines how to use these relationships for automated threat identification or to support human analysts, like how police use notice boards with photos and wires. The primary focus is on expressing relationship data as massive graphs, with additional interest in incorporating tabular, language, and unstructured data.
What you’ll 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 software engineering teams and customers to understand project requirements. 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 fieldProficient 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 scikit-learn, Pandas, PyTorch, (py)Spark will boost the start Why Cisco
At Cisco, each person brings their unique talents to work as a team and make a difference. Yes, our technology changes the way the world works, lives, plays and learns, but our edge comes from our people.
We connect everything – people, process, data and things – and we use those connections to change our world for the better.
We innovate everywhere - From launching a new era of networking that adapts, learns and protects, to building Cisco Services that accelerate businesses and business results. Our technology powers entertainment, retail, healthcare, education and more – from Smart Cities to your everyday devices.
We benefit everyone - We do all of this while striving for a culture that empowers every person to be the difference, at work and in our communities.
Colorful hair? Don’t care. Tattoos? Show off your ink. Like polka dots? That’s cool. Pop culture geek? Many of us are. Be you, with us! #WeAreCisco.
#jtstandard
Who You’ll Work With
We are a bunch of a former security startups collectively called Threat Detection and Response. We keep an agile, fun, 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.
Who You Are
We are seeking a motivated Machine Learning Researcher 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:
Similarity Search on Sequence of Endpoint Security Events – Each monitored device in a computer network outputs streams of cybersecurity events. This project focuses on finding common patterns in these streams to identify similarly behaving devices using similarity search techniques. The data stream is segmented into sequences of related events, which are then represented in an embedding space to identify similar sequences.
Advance Command Line Preprocessing – Building a robust system to correlate individual cybersecurity events into incidents requires understanding the activity on impacted devices rather than just matching parameters. This project focuses on understanding and normalizing command lines leading to cybersecurity events. Command lines often contain specific parameters like usernames, hashes, or random strings that obscure their functionality. Removing or masking these values can help uncover similar patterns across different devices or environments, providing robust similarity measures between cybersecurity events.
Learning on Cybersecurity Relational Data – Cybersecurity investigations often rely on relationships between entities like IP addresses, URLs, email addresses, documents, binaries, and internet users. This project examines how to use these relationships for automated threat identification or to support human analysts, like how police use notice boards with photos and wires. The primary focus is on expressing relationship data as massive graphs, with additional interest in incorporating tabular, language, and unstructured data.
What you’ll 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 software engineering teams and customers to understand project requirements. 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 fieldProficient 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 scikit-learn, Pandas, PyTorch, (py)Spark will boost the start Why Cisco
At Cisco, each person brings their unique talents to work as a team and make a difference. Yes, our technology changes the way the world works, lives, plays and learns, but our edge comes from our people.
We connect everything – people, process, data and things – and we use those connections to change our world for the better.
We innovate everywhere - From launching a new era of networking that adapts, learns and protects, to building Cisco Services that accelerate businesses and business results. Our technology powers entertainment, retail, healthcare, education and more – from Smart Cities to your everyday devices.
We benefit everyone - We do all of this while striving for a culture that empowers every person to be the difference, at work and in our communities.
Colorful hair? Don’t care. Tattoos? Show off your ink. Like polka dots? That’s cool. Pop culture geek? Many of us are. Be you, with us! #WeAreCisco.
#jtstandard
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