AI Research Engineer at Sonar

Position Overview

• Location Type: Hybrid
• Employment Type: Full-time
• Salary: (Not provided)

Sonar is a company dedicated to helping organizations build responsible, secure, and high-quality code. This AI Research Engineer role offers the opportunity to conduct cutting-edge research, develop novel algorithms, and contribute to developing software tools that enhance system performance, reliability, and flexibility. The role focuses on integrating AI and LLM techniques with software engineering practices.

Requirements

• Education: Master’s degree (or equivalent) in Computer Science, Engineering, or a related field.
• Experience: At least 3 years of experience as an ML/AI/LLM Engineer or AI Scientist, ideally within Software Engineering.
• Research Background: Strong research background in AI, ML, and Software Engineering.
• Generative AI Technologies: Experience working with generative AI technologies (e.g., GPT-4, BedRock).

Responsibilities

• Applied Research: Conduct applied research in integrating AI/LLM techniques with software engineering practices to improve code quality, testing, and software maintenance.
• Prototyping: Design and implement experimental prototypes to demonstrate the feasibility of new methodologies.
• LLM Training & Fine-tuning: Train and fine-tune LLMs (both commercial and open-source) to improve performance.
• Data Collection & Preprocessing: Implement and maintain pipelines to collect high-quality large datasets for training/fine-tuning LLMs.
• Data Analysis: Prepare, analyze, and preprocess large datasets of code used to train LLMs.
• Collaboration: Collaborate with cross-functional teams, including software engineers and product managers, to translate research findings into practical applications.
• Staying Informed: Stay informed about the latest advancements in AI/ML and software engineering to identify emerging trends and opportunities for innovation.
• Code Review & Feedback: Participate in code reviews and provide constructive feedback to other developers/researchers.
• Best Practices: Implement best practices from DevOps to maintain a readable codebase, testable infrastructure, and documented research artifacts.

Application Instructions

• (Not provided)

Company Information

• Culture: Dynamic culture with employees worldwide and hub offices in the USA, Switzerland, the UK, Singapore, and Germany.
• Mission: Provide solutions that deliver Clean Code.
• Impact: Work on pioneering projects that advance the application of AI and ML within software engineering, directly impacting the efficiency and effectiveness of AI products.