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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.

We are looking for an ML Engineer to support AI research and development, focusing on experimenting, deploying and scaling ML models (especially LLMs). As part of our AI Core Team, you will enable cutting-edge research to transition smoothly into production-ready AI features. You will work at the intersection of AI research and engineering, ensuring that ML models can be efficiently deployed, tested, and iterated.

The impact you will have

You will pave the way for AI innovation by developing efficient, scalable, and reliable ways to deploy and manage machine learning models. Your work will enable our AI researchers and software engineers to iterate faster, explore new ideas, and bring AI-powered features into Sonar products. By optimizing the end-to-end ML lifecycle, you will directly contribute to the next generation of AI-driven developer tools.

On a daily basis, you will

Collaborate with AI researchers and engineers to bridge the gap between research and production.
Deploy, manage, and monitor LLM/ML models in both cloud and on-premise environments, ensuring smooth integration into our research and production pipelines.
Support engineers in integrating ML models into production, ensuring a smooth handoff from research to product teams.
Automate ML workflows with CI/CD pipelines for model deployment and continuous integration.
Design and maintain flexible ML workflows to support rapid experimentation.
Enable fast iteration by setting up tools for model tracking, logging, and comparison (e.g., MLflow, DVC, Weights & Biases).
Manage research-friendly cloud environments that allow easy deployment and experimentation.
Optimize model inference for speed, efficiency, and scalability while balancing research flexibility.
Ensure AI models and experiments are reproducible by structuring model storage, versioning, and benchmarking practices.

The skills you will demonstrate

Academic background with a university degree in Computer Science, software engineering, Machine Learning, or a related field.
Strong programming skills in Python (PyTorch, TensorFlow, Hugging Face, LangChain, FastAPI, Flask).
Good understanding of ML model architecture and LLMs, including how they are trained, fine-tuned, and deployed on AWS platform.
Familiarity with distributed model training and model optimization.
Experience deploying ML models and LLMs in cloud environments and local environments.
Proficiency with AWS infrastructure, including EC2, S3, SageMaker and Bedrock.
Ability to build effective ML pipelines for research and development.
Experience with ML model lifecycle tools (e.g., MLflow, DVC, Weights & Biases).
Proficiency with DevOps/MLOps best practices, including CI/CD, version control (Git), docker and IaC.
Excellent problem-solving skills, with the ability to troubleshoot performance bottlenecks in ML pipelines.
Fluent in English, with the ability to communicate complex technical topics effectively.

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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Senior Machine Learning Engineer

Senior Machine Learning Engineer

Sonar

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