Staff Data Scientist

In the cloud, every second counts. On the leading edge of security, Sysdig stops attacks in real time by instantly detecting changes in cloud security risk with runtime insights and open source Falco. We are passionate open source enthusiasts at heart and technical problem-solvers who are continually innovating and delivering powerful solutions to secure cloud-native applications.

We value diverse opinions and open dialogue to spur ideas. We believe in working closely together to achieve our goals, and since our launch, we have been flexible with when and where we work. We’re an international company that understands how to cultivate a strong culture across remote teams. 

And we’re a great place to work too – we’ve been named a “Best Place to Work” by Inc., the San Francisco Business Times and the Silicon Valley Business Journal, and we won six workplace awards from Comparably this year. We have been recognized by Deloitte as one of the 500 fastest-growing organizations for the last four years. 

We are looking for driven team members who want to join us on our mission to lead cloud security globally. Does this sound like the right place for you?

What you will do

• Work with product team to understand customer’s pain points and define problem statements
• Evaluate state of art and assess the feasibility of different machine learning models.
• Define rigorous research plan and experimental protocol. Manage end-to-end machine learning projects, from business requirements to actual collaboration with ML engineers for production release
• Design ML algorithms and perform model assessment
• Communicate the results across several stakeholders and support decision making
• Provide feedbacks, review research plans, and actively collaborate with other data scientists in the domain of Generative AI, time series analysis, and anomaly detection
• Stay up to date of the most recent advancements in AI/ML research through papers and publications
• Embrace a startup mindset to drive innovation and agility within the organization

What you will bring with you

• Experience in leading data science projects
• Experience in Machine Learning and principal scientific packages (e.g. Pytorch, Tensorflow, Keras, Scikit, Pandas, etc)
• Experience with most relevant Generative AI frameworks (langchain, openai, anthropic, …)
• Experience with at least one programming language (e.g. Python, Go)

What we look for

• 5+ years of experience in a relevant role
• PhD degree in Machine Learning, Statistics, Computer Science, Physics or other relevant fields
• Ability to conduct independent applied research in cyber attacks detection
• Strong background in deep learning, time series analysis, anomaly detection, and NLP
• Strong Scientific skills
• Strong Programming skills
• Comfort with startup environment

Why work at Sysdig?

• We’re a well-funded, fast-growing company that has a large enterprise customer base.
• We have a pragmatic and transparent culture from the CEO down.
• We are leading the cloud security market.
• Our open source tools (https://sysdig.com/opensource/) are widely used and loved by technologists and developers.

When you join Sysdig, you can expect:

• Competitive compensation, including equity opportunities.
• An international culture with employees in more than 40 countries.
• Flexible work arrangements.
• Mental well-being support for you and your family, a wellness alliance, and company-wide recharge days.
• Career growth and development opportunities.

We would love for you to join us! Please reach out even if your experience doesn’t perfectly match the job description. We can always explore other options after starting the conversation. Your background and passion will set you apart, especially if your career is unconventional.

Sysdig values a diverse workplace and strongly encourages women, people of color, LGBTQIA+ individuals, people with disabilities, members of ethnic minorities, foreign-born residents, and veterans to apply. Sysdig is an equal-opportunity employer. Sysdig does not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, sexual orientation, gender identity, or any other legally protected status.

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