At a Glance
- Tasks: Join a team innovating enterprise-grade coding agents and models using cutting-edge research.
- Company: Sonar, a leader in static analysis and AI solutions.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and learning.
- Why this job: Be hands-on with state-of-the-art research and make a real impact on coding practices.
- Qualifications: Master’s or PhD in Computer Science, strong ML experience, and Python fluency.
The predicted salary is between 60000 - 80000 £ per year.
Requirements
- An advanced academic background (Master’s or PhD) in Computer Science, Machine Learning, or a related quantitative field
- Strong industry experience in machine learning, with a solid understanding of modern software engineering practices and tools
- Fluency with Python including core ML frameworks; experience with Rust or any of SonarQube’s flagship languages (C#, C++, JS/TS, Java) is a plus
- Expertise in post‑training of AI models, with techniques such as:
- Reinforcement learning from verifiable rewards
- GRPO and related techniques
- Offline or semi‑online reinforcement learning
- Parameter efficient fine‑tuning
- Supervised fine‑tuning
- Safety Alignment
- Experience with large‑scale data processing frameworks and cloud infrastructure (e.g. AWS, Microsoft Foundry, Databricks)
- Experience of driving research projects, delivering valuable findings and prototypes, and then converting them into products
- Excellent communication skills in English and a talent for explaining complex scientific topics clearly and concisely
What the job involves
- At Sonar, we are seeking an ambitious research engineer to join our cross‑disciplinary team, innovating and developing the next generation of solutions to build enterprise‑grade coding agents and models.
- You will harness Sonar’s deep experience in static analysis, and combine it with your experience and leading techniques in large language model post‑training.
- If you are interested in being hands‑on with state‑of‑the‑art research, building practical solutions that deliver high‑impact for customers, and working within a team of innovative researchers and engineers, this role is for you.
- Outcome Driven Development: Work in a team developing and implementing advanced products that enable customers to post‑train models to power their agentic coding practices. These agents need to generate high‑quality code that meets their enterprise standards and software development best practices.
- Translate Prototypes to Products: Collaborate closely with researchers, research engineers, MLOps and Engineers within the team to design hypotheses and experiments, iterate proofs‑of‑concept quickly and develop successful prototypes into cutting‑edge products.
- Subject Matter Expert: You will contribute and discuss ideas within our cross‑disciplinary team, driving towards the next generation of coding model post‑training for enterprises.
- Spearhead Research & Innovation: Stay up‑to‑date with the latest LLM and agentic developments; you are driven by learning and teaching others. You will need to explain complex technical details and concepts to both technical and non‑technical audiences.
Research Engineer (Post-Training for Agentic Coding) employer: SonarSource
At Sonar, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. Our team-oriented environment encourages continuous learning and professional growth, providing ample opportunities for research engineers to develop cutting-edge solutions in a supportive setting. Located in a vibrant tech hub, we offer competitive benefits and the chance to work with industry leaders, making a meaningful impact in the world of AI and coding.
StudySmarter Expert Advice🤫
We think this is how you could land Research Engineer (Post-Training for Agentic Coding)
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or conferences related to machine learning and coding. You never know who might be looking for someone just like you!
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving post-training of AI models. Share your GitHub link when networking or during interviews to give potential employers a taste of what you can do.
✨Ace the Interview
Prepare for technical interviews by brushing up on your Python and ML frameworks. Practice explaining complex concepts clearly, as communication is key in this role. Mock interviews can help you get comfortable!
✨Apply Through Us!
Don’t forget to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Research Engineer (Post-Training for Agentic Coding)
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your advanced academic background and industry experience in machine learning. We want to see how your expertise aligns with the role, so don’t hold back on showcasing your Python fluency and any experience with Rust or other relevant languages.
Be Clear and Concise:When explaining your experience with AI model post-training techniques, keep it straightforward. We appreciate clarity, especially when discussing complex topics, so aim for a balance between detail and simplicity.
Tailor Your Application:Customise your application to reflect our job description. Mention specific projects where you’ve driven research or developed prototypes, and how they relate to building enterprise-grade coding agents. This shows us you’re genuinely interested in the role!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at StudySmarter!
How to prepare for a job interview at SonarSource
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning and software engineering practices. Be ready to discuss your experience with Python and any other relevant languages like Rust or C#. Familiarise yourself with the latest techniques in AI model post-training, as this will show your passion and expertise.
✨Showcase Your Projects
Prepare to talk about specific research projects you've worked on. Highlight how you drove these projects from concept to product, focusing on the impact they had. Use concrete examples to demonstrate your ability to deliver valuable findings and prototypes.
✨Communicate Clearly
Since you'll need to explain complex topics to various audiences, practice articulating your ideas clearly and concisely. Think about how you can break down intricate concepts into simpler terms, especially for non-technical stakeholders.
✨Stay Current
Keep yourself updated on the latest developments in large language models and agentic coding. Being able to discuss recent trends or breakthroughs in the field will not only impress your interviewers but also show that you're genuinely interested in the role and the industry.
