At a Glance
- Tasks: Join a team innovating enterprise-grade coding agents and models using cutting-edge AI techniques.
- Company: Sonar, a global leader in software development solutions with a focus on diversity and inclusion.
- Benefits: Competitive salary, inclusive culture, and opportunities for hands-on research and innovation.
- Other info: Dynamic environment with excellent career growth and a commitment to diversity.
- Why this job: Make a real impact by developing advanced AI solutions that enhance coding practices.
- Qualifications: Master’s or PhD in Computer Science or related field; strong machine learning and software engineering skills.
The predicted salary is between 60000 - 80000 £ per year.
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.
What you will do
- 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: 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; drive learning and teach others. Explain complex technical details and concepts to both technical and non‑technical audiences.
Experience and qualifications
- 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 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.
We value diversity, equity, and inclusion
At Sonar, we believe that our diversity is our strength. We are a global company that values and respects different backgrounds, perspectives, and cultures. We are committed to fostering a diverse and inclusive work environment where everyone feels valued and empowered to contribute their best. We are proud to be an equal opportunity employer and welcome all qualified applicants, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
If you need any accommodation, please reach out to us at hiring@sonarsource.com. All offers of employment at Sonar are contingent upon the results of a comprehensive background check and reference verification conducted before the start date. We do not currently support visa candidates in the US. Applications that are submitted through agencies or third‑party recruiters will not be considered.
AI Research Engineer - Post-Training employer: Sonar
At Sonar, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. Our commitment to diversity, equity, and inclusion ensures that every team member feels valued and empowered to contribute their unique perspectives. With ample opportunities for professional growth and hands-on experience in cutting-edge AI research, joining our team means being part of a forward-thinking company dedicated to making a meaningful impact in the tech industry.
StudySmarter Expert Advice🤫
We think this is how you could land AI Research Engineer - Post-Training
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Sonar!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI Research Engineer - Post-Training at Sonar.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Sonar.
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We think you need these skills to ace AI Research Engineer - Post-Training
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Sonar, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Sonar. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Sonar
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Sonar!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
