Interested in delivering large scale distributed software systems using cutting edge technologies in a culture that encourages autonomous productive teams? Interested in building software that mines large volumes of network data to detect anomalies and malware? Be a part of Qualys Network Security, a team of software engineers innovating network security in the next generation Qualys Technology Platform.
- Develop algorithms that solve problems with multiple data dimensions each with million to billion data points, in a computationally efficient manner.
- Take end to end ownership of Machine Learning Systems.
- Understand data networking in office, industrial, home and IoT domains, identify data dimensions that can be exploited, build tools collect and normalise the data with appropriate labels.
- Build and train multiple machine models efficiently with the collected data.
- Implement robust production software using these machine models to process customer data and provide them insights and analytics to secure their networks.
- Implement continuous improvements to the machine models by continuous analysis of data collected from customer networks.
- Candidate should have a minimum of one year’s experience with Machine Learning algorithms, a strong technical ability, good communication skills using professional documentation tools, and ability to collaborate using tools like Zoom/Google-Meet and strong motivation to work remotely and achieve results in a fast paced environment.
- Candidates who have experience in implementing Python based micro-services in a SaaS architecture and/or have completed Andrew Ng's course in Coursera and/or have completed Google's crash course in Machine learning will have a distinct advantage.
- Excellent programming and designing skills in Python, Tensorflow coupled with good analytical skills for problem solving.
- Good understanding of basic networking concepts, operating system fundamentals, data structures and algorithms