LLM Data Researcher
Turing- Full Time
- Junior (1 to 2 years)
Candidates should possess a Master's degree (or equivalent) in Computer Science, Engineering, or a related field, and at least three years of experience as an ML/AI/LLM Engineer, ideally within a Software Engineering context. A strong research background in Artificial Intelligence, Machine Learning, and Software Engineering is required, along with experience working with generative AI technologies such as GPT-4 and BedRock.
The LLM Engineer will conduct applied research in integrating AI/LLM techniques with software engineering practices to improve code quality, testing, and software maintenance. They will also design and implement experimental prototypes, train and fine-tune LLMs, implement and maintain data pipelines, prepare and analyze large datasets of code, collaborate with cross-functional teams, stay informed about advancements in AI/ML, and participate in code reviews while implementing best practices from DevOps.
Tools for code quality and security
SonarSource provides tools aimed at improving code quality and security for software developers. Its main products include SonarLint, an IDE plugin that gives real-time feedback on code quality; SonarQube, a self-managed solution for comprehensive code analysis and reporting; and SonarCloud, a cloud-based service that offers similar features with the convenience of cloud management. SonarSource operates on a subscription-based model, allowing clients to access its tools through annual subscriptions or usage-based pricing for cloud services. The company serves over 400,000 organizations worldwide, emphasizing the importance of writing clean, maintainable, and secure code. SonarSource's goal is to promote the philosophy of "Clean Code," which enhances the efficiency of development teams and improves the security and reliability of software applications.