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AI Engineer

Why should I Apply:


At Sonar, we’re a group of brilliant, motivated, and driven professionals working hard to help organizations build responsible, secure, high-quality code quickly and systematically. We build solutions that don’t just solve symptoms of problems – we fix problems at the source – source code, to be specific.


We have a dynamic culture with employees worldwide and hub offices in the USA, Switzerland, the UK, Singapore, and Germany. We believe team members should have the opportunity to come to work every day, work on a product they are proud of, love what they do, and feel energized by their peers. With our roots deep in the open source community, we’re all about the mission: provide solutions that deliver Clean Code.


The impact you will have 

 

You will work on pioneering projects that advance the application of AI and ML within software engineering. 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. Your work as an AI Engineer will directly impact the efficiency and effectiveness of our AI products, enabling developers to spend less time fixing issues and more time innovating. You will contribute to creating accessible, user-friendly, and performant solutions that integrate seamlessly with our existing infrastructure.


On a daily basis, you will
  • Conduct applied research in integrating AI/LLM techniques with software engineering practices to improve code quality, testing, and software maintenance.
  • Design and implement experimental prototypes to demonstrate feasibility of new methodologies.
  • Training and fine-tuning LLMs (both commercial and open-source) to improve performance
  • Implement and maintain pipelines to collect high quality large datasets to train/finetune LLMs. 
  • Prepare, analyze and preprocess large datasets of code used to train LLMs
  • Collaborate with cross-functional teams, including software engineers, and product managers, to translate research findings into practical applications.
  • Stay informed about the latest advancements in AI/ML and software engineering to identify emerging trends and opportunities for innovation.
  • Participate in code reviews and provide constructive feedback to other developers/researchers. 
  • Implement best practices from DevOps to maintain a readable codebase, testable infrastructure and documented research artifacts


The skills you will demonstrate
  • Masters degree (or equivalent)  in Computer Science, Engineering, or related field.  
  • At least 3 years of experience as a ML/AI/LLM Engineer or AI Scientist, ideally in Software Engineering.
  • Strong research background in AI, ML, and SE 
  • Experience working with generative AI technologies (e.g. GPT-4, BedRock) 
  • Experience in developing tools or frameworks that utilize AI/ML to enhance software development processes.
  • Familiarity with techniques for automated code generation, program synthesis, and software testing using AI/ML
  • Experience in developing and prototyping in Python and R
  • Understanding of software development processes and terminology.
  • Excellent debugging, optimization skills, communication and teamwork skills
  • Excellent problem-solving skills and the ability to work independently or as part of a team.


Nice to have
  • Knowledge of reinforcement learning algorithms and experience with model training
  • Experience in publishing research papers in top-tier conferences and journals
  • Familiarity with AWS services such as Lambda, EC2, ECS, SNS, SQS, and RDS is an advantage
  • Experience using and configuring static analyzers as part of a research project


Why you will love it here:


Our culture and mission set us apart. We have a dynamic work culture that values respect and kindness – and embraces the right to fail (and get right back up again!). We believe that the best idea wins and everyone has a voice.

We believe that great people make a great company. We value people skills as much as technical skills and strive to keep things friendly and laid-back while still being passionate leaders in our domains. Our 550+ SonarSourcers from 33 different nationalities can relate!

We embrace work-life balance. It is important to maintain a healthy work-life balance. This is why we have a flexible work policy that includes remote and in-office hybrid work (minimum three days a week in the office - Monday/Tuesday/Thursday).

We have a growth mindset. We love to learn and believe that continuous education is critical to our success. In an ever-changing industry, new skills are a must, and we're happy to help our team acquire them.



We prioritize Diversity, Equity, and Inclusion:


At Sonar, we are a global workforce and recognize the value of different backgrounds, and global cultures.


We are committed to creating a diverse work environment and are proud to be an equal-opportunity employer. All qualified applicants will be considered for employment without regard to race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.


All offers of employment at Sonar are contingent upon the clear results of a comprehensive background check conducted prior to the start date.


Please note that applications submitted through agencies or third-party recruiters will not be considered.

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CEO of Sonar
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Olivier Gaudin
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Average salary estimate

$100000 / YEARLY (est.)
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What You Should Know About AI Engineer, Sonar

Are you passionate about combining artificial intelligence with software engineering? At Sonar, we're on the lookout for an AI Engineer to join our vibrant team in Singapore. Our mission revolves around creating tools that not only tackle problems at their roots but also revolutionize the way developers approach coding. As an AI Engineer, you’ll dive deep into groundbreaking projects that blend AI and software engineering. Your work will influence how we enhance code quality and optimize software processes, allowing developers to be more innovative rather than just problem-solvers. You’ll be conducting research, designing experimental prototypes, and collaborating with cross-functional teams to translate technical findings into real-world applications. Your hands will be on the latest AI techniques, including generative AI technologies and model training, enabling you to boost system performance and reliability significantly. With a flexible workplace and growth mindset, we prioritize not just what you do, but how you fit into our dynamic culture that values teamwork, innovation, and continuous learning. If you’re ready for a challenge that promotes not just your career but also a positive work-life balance, Sonar is the place for you. Join us and help shape the future of coding with cutting-edge AI solutions that make a real impact!

Frequently Asked Questions (FAQs) for AI Engineer Role at Sonar
What responsibilities does an AI Engineer have at Sonar?

As an AI Engineer at Sonar, you will engage in research and development, focusing on integrating AI and ML techniques to transform software engineering practices. Your tasks will include conducting applied research, designing prototypes, training large language models (LLMs), and collaborating with software engineers and product managers to implement your findings. You'll be responsible for enhancing code quality and ensuring that developers can innovate without the burden of fixing issues.

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What qualifications are needed to become an AI Engineer at Sonar?

To land the AI Engineer position at Sonar, candidates are expected to have a Master’s degree in Computer Science or a related field, along with at least three years of experience in AI, ML, or LLM engineering. A strong foundation in software engineering, hands-on experience with generative AI technologies, and proficiency in programming languages like Python and R are also crucial.

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How does Sonar support professional growth for AI Engineers?

Sonar is committed to fostering a growth mindset among its employees, especially in roles like AI Engineer. We provide continuous education opportunities and encourage team members to learn new skills relevant to their roles. With a culture that values respect and collaboration, you'll find ample support to expand your expertise in AI and software engineering.

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What tools and technologies will an AI Engineer at Sonar work with?

In your role as an AI Engineer at Sonar, you'll utilize a variety of tools and technologies, including but not limited to Python, R, and frameworks suitable for AI model training. Additionally, familiarity with AWS services such as Lambda, EC2, and SQS would be advantageous, alongside experience in automated code generation and testing using AI/ML techniques.

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What is the team culture like for AI Engineers at Sonar?

The culture at Sonar is dynamic and inclusive, emphasizing teamwork, respect, and an openness to failure. As an AI Engineer, you will be part of a diverse team that values both technical prowess and interpersonal skills. Our flexible work policy also ensures a healthy work-life balance, with an environment where your voice is heard, fostering creativity and collaboration.

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Common Interview Questions for AI Engineer
Can you describe your experience with machine learning algorithms and how you have applied them in software engineering?

In responding to this question, focus on specific algorithms you have utilized, the problems they addressed, and the results achieved. Discuss practical applications, such as improving code quality or optimizing performance, and emphasize your analytical approach and outcomes from those projects.

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How do you approach conducting research in AI, particularly within the software engineering domain?

Highlight your research methodology, how you identify relevant problems, and your approach to experimentation. Discuss any literature reviews you perform, the tools you employ for research, and how you collaborate with peers to validate your findings or develop practical applications.

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What generative AI technologies have you worked with, and what was your experience with them?

Be specific about the generative AI technologies you've used, such as GPT-4 or BedRock. Describe projects where you implemented these technologies, the challenges you faced, and how you overcame them to achieve successful outcomes in software development or quality improvement.

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Can you share an example of how you've contributed to improving system performance in a previous role?

Provide a concrete example illustrating the measures you took to enhance system performance, the techniques you employed, and the results of your efforts. Mention tools or methodologies that were instrumental in your contribution and the overall impact on the project.

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How do you ensure the quality and reliability of AI models you develop?

Discuss methods you use for validating AI models, such as testing frameworks or performance benchmarks. Highlight practices around documentation, continuous integration, and peer code reviews that aid in maintaining the reliability and quality of your models.

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What do you believe are the key challenges of integrating AI in software development?

Look at this question holistically by noting challenges like data quality, the need for domain expertise, and potential biases in AI systems. Provide thoughtful opinions on how you've tackled these challenges in past experiences and your commitment to navigating them effectively.

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How do you keep up with the latest trends in AI/ML and software engineering?

Explain the strategies you use for continuous learning, such as following industry trends, reading academic papers, participating in webinars, or attending conferences. Emphasize how you apply new knowledge to your work and share insights with your team to foster a collaborative learning environment.

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Can you explain your experience with data preprocessing for AI training?

Detail your methods for data collection, cleaning, and preprocessing. Explain the importance of high-quality datasets in training AI models and share examples of specific challenges you've faced in this area and how you've successfully navigated them.

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Describe how you collaborate with cross-functional teams in your projects?

Discuss the importance of teamwork within software development and how you establish effective communication with stakeholders from different departments. Cite examples where your collaboration led to successful project outcomes and innovations.

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What are your thoughts on the ethical implications of AI in software engineering?

Show that you are aware of the broader context surrounding AI and discuss ethical considerations, such as bias, transparency, and accountability. Articulate your views on responsible AI practices and how you aim to contribute positively in your role as an AI Engineer.

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As a company, we aim to have every developer and development team using our products for their code quality and security. The founders believed that building a great place to work with a strong culture would help us make this goal come true in fos...

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Full-time, hybrid
DATE POSTED
April 17, 2025

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