ReversingLabs was founded in 2009 with the mission of offering organizations the ultimate in threat detection solutions. In 2017, we were honored to receive the JPMorgan Chase Hall of Innovation Award for our truly unique, automated, and scalable static file analysis, malware classification and malware hunting technologies. Our pioneering technologies, exceptional products, and successful customer deployments also drove a $25 million investment in ReversingLabs, backed by some of the savviest investors in the world. With our center of development excellence located in Zagreb, and offices in the United States and Switzerland, ReversingLabs is poised to achieve rapid growth and deliver groundbreaking innovation in 2021.
Our team works on static file analysis. This involves identification, unpacking, metadata extraction and classification. The technologies we develop are applied on millions of new files daily and we have vast amounts of metadata to dig through and look for errors, interesting samples and novel malware.
You are ideally an undergraduate in a technology-oriented study program and you can write simple automation scripts. Your role would revolve around data analysis or data quality, and you would help us analyze the data we have to generate insights and find various kinds of important samples. That includes manual inspection of some kinds of files to check for possible mistakes in detection and to curate labels in machine learning datasets.
You can expect to learn many tricks for working with data, and pick up some more advanced data science techniques, as well as machine learning knowledge. Finding new solutions to security problems is very challenging and interesting.
- familiarity with GNU/Linux command-line tools (grep, xargs, sort, rsync, …),
- basic knowledge of Python or Bash scripting,
- basic knowledge of SQL,
- interest in information security in general, e.g. do you know the difference between a trojan and ransomware?
enthusiasm for learning new things, teamwork, and a self-starter attitude.
Big plus if:
- you have previously worked with the Python data stack (numpy, pandas, scikit-learn),
you are familiar with machine learning concepts.
- working with cutting-edge technologies and involvement in research projects as an equal team member,
- flexible working hours depending on your university responsibilities. Your education should come first,
perks of our Zagreb office: free coffee, beverages and cookies, mingling and relaxation areas, sports activities, access to technical literature, and more.
During your studies, the working hours are adapted to your schedule, but 50% of full-time employment is desirable. Undergraduate and first-year graduate students are preferred because we expect a long-term commitment, integration within the team, and growing responsibilities with progressively more challenging tasks.