MACHINE LEARNING ENGINEER
Why should I Apply:
At Sonar, we’re a group of brilliant, motivated, and driven professionals working hard to help organizations build responsible, secure, high-quality code quickly and systematically. We build solutions that don’t just solve symptoms of problems – we fix problems at the source – source code, to be specific.
We have a dynamic culture with employees worldwide and hub offices in the USA, Switzerland, the UK, Singapore, and Germany. We believe team members should have the opportunity to come to work every day, work on a product they are proud of, love what they do, and feel energized by their peers. With our roots deep in the open source community, we’re all about the mission: provide solutions that deliver Clean Code.
Sonar solves the trillion-dollar challenge of bad code. Sonar equips organizations to achieve and sustain a Clean Code state by empowering developers to write consistent, intentional, adaptable, and responsible code. Clean Code produces software that is maintainable, reliable, and secure, allowing development teams to spend less time fixing issues and more time innovating. With Sonar, and by employing the company’s Clean as You Code methodology, organizations minimize risk, reduce technical debt, increase productivity, and derive more value from their software in a predictable and sustainable way.
Sonar’s open-source and commercial products – SonarLint, SonarCloud, and SonarQube – support over 30 programming languages, frameworks, and infrastructure technologies. Trusted by more than 500,000 organizations and used by more than 7 million developers globally to clean more than half a trillion lines of code, Sonar is integral to delivering better software.
Sonar is looking for a passionate Machine Learning Scientist who loves to explore ways to improve our products by combining static code analysis with machine learning. You will be part of our Research & Development team that drives the innovation of our code analysis technologies.
What your future team would like you to know
The R&D team is a new team at SonarSource established after the acquisition of RIPS Technologies. RIPS was known as a technology leader in static application security testing and for its fast and accurate SAST approach. With joint forces and tech expertise at SonarSource, we continue to provide the leading code analysis products for developers. Join us in this fun adventure and take a unique opportunity to help build the best code analyzers in the world!
The impact you will have
With your domain expertise and experience you will shape an innovative R&D team at Sonar. You will explore state-of-the-art approaches and new ideas that help to push our code analysis technology and features beyond the limits. By implementing and testing visionary prototypes, you are preparing the next generation of our cutting-edge products that are loved by millions of developers around the globe.
In this role, you can expect to
- Have fun in a creative team that shares your passion and interest in code analysis technologies
- Stay up-to-date with the latest academic research and industry trends related to machine learning and deep learning on code
- Understand the inner workings and limitations of our static analysis technologies
- Identify, discuss, and qualify new innovation opportunities using ML that are feasible in practice and applicable to our products
- Automate data gathering to build specialized ML models that advance our technologies
- Prototype and evaluate new ML models that solve real-world problems and satisfy our customer needs
The skills you will demonstrate
- You have a scientific background by receiving a doctorate or master’s degree in computer science or a related field
- You have practical industry experience in software development and a solid understanding of software engineering concepts, workflows, and tools
- You have solid programming skills in Python; experience with Java is a plus
- You have basic knowledge of large-scale data processing and related data infrastructure (AWS)
- You have hands-on experience with implementing various state-of-the-art ML/DL techniques, ideally for NLP or PLP
- Basic knowledge of common code issues (bugs, errors, vulnerabilities) and parsing code is a plus
- You can think outside the box and turn abstract, theoretical ideas into practical, feasible solutions for our users autonomously
- You are fluent in English, both written and spoken, and are able to understand and explain complex technical and scientific topics
Why you will love it here:
• Our culture and mission set us apart. We have a dynamic work culture that values respect and kindness – and embraces the right to fail (and get right back up again!). We believe that the best idea wins and everyone has a voice.
• We believe that great people make a great company. We value people skills as much as technical skills and strive to keep things friendly and laid-back while still being passionate leaders in our domains. Our 550+ SonarSourcers from 33 different nationalities can relate!
• We embrace work-life balance. It is important to maintain a healthy work-life balance. This is why we have a flexible work policy that includes remote and in-office hybrid work (minimum three days a week in the office - Monday/Tuesday/Thursday).
• We have a growth mindset. We love to learn and believe that continuous education is critical to our success. In an ever-changing industry, new skills are a must, and we're happy to help our team acquire them.
We prioritize Diversity, Equity, and Inclusion:
At Sonar, we are a global workforce and recognize the value of different backgrounds, and global cultures.
We are committed to creating a diverse work environment and are proud to be an equal-opportunity employer. All qualified applicants will be considered for employment without regard to race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
All offers of employment at Sonar are contingent upon the clear results of a comprehensive background check conducted prior to the start date.
