At a Glance
- Tasks: Join a team innovating AI solutions and develop enterprise-grade coding agents.
- Company: Sonar, a leader in static analysis and AI research.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Collaborative team culture focused on innovation and learning.
- Why this job: Be hands-on with cutting-edge research and make a real impact in AI development.
- Qualifications: Advanced degree in Computer Science or related field, with strong ML experience.
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.
AI Research Engineer (Post-Training) employer: SonarSource
At Sonar, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to push the boundaries of AI research. As an AI Research Engineer, you will have access to cutting-edge technology and resources, along with ample opportunities for professional growth and development in a supportive environment. Located in a vibrant tech hub, our team thrives on creativity and teamwork, making it an ideal place for those looking to make a meaningful impact in the field of machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land AI Research Engineer (Post-Training)
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or conferences related to AI and machine learning. You never know who might be looking for someone with your skills, and personal connections can often lead to job opportunities.
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving post-training techniques or large-scale data processing. Having tangible examples of your work can really impress potential employers and give them a taste of what you can bring to the table.
✨Ace the Interview
Prepare for technical interviews by brushing up on your knowledge of reinforcement learning and other relevant techniques. Practice explaining complex concepts clearly, as communication is key in this role. Remember, they want to see how you think and solve problems!
✨Apply Through Our Website
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, it shows you’re genuinely interested in joining our innovative team at Sonar.
We think you need these skills to ace AI Research Engineer (Post-Training)
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 post-training techniques, keep it straightforward. We appreciate clarity, especially when discussing complex topics like reinforcement learning or parameter-efficient fine-tuning. Remember, we’re looking for someone who can communicate effectively!
Tailor Your Application:Don’t just send a generic application! Tailor your CV and cover letter to reflect how your skills and experiences make you a perfect fit for our team at Sonar. Mention specific projects or achievements that relate to the job description.
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 shows you’re keen on joining our innovative team!
How to prepare for a job interview at SonarSource
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning techniques, especially those related to post-training. Be ready to discuss reinforcement learning and parameter-efficient fine-tuning in detail, as these are key areas for the role.
✨Showcase Your Projects
Prepare to talk about your past projects, particularly those where you've driven research or developed prototypes. Highlight how you turned ideas into products, and be specific about the impact your work had on previous teams or customers.
✨Communicate Clearly
Since you'll need to explain complex concepts to various audiences, practice articulating your thoughts clearly and concisely. Use examples from your experience to illustrate your points, making it easier for interviewers to grasp your expertise.
✨Stay Current
Keep yourself updated with the latest trends in AI and large language models. Being able to discuss recent developments shows your passion for the field and your commitment to continuous learning, which is something that will impress the interviewers.
