ML Ops Engineer
Sonar Source
Job Summary
Sonar is seeking an ML Ops Engineer to support AI research and development, with a focus on experimenting, deploying, and scaling ML models, especially LLMs. The role involves enabling cutting-edge research to transition into production-ready AI features, working at the intersection of AI research and engineering. The engineer will develop efficient, scalable, and reliable ways to deploy and manage machine learning models, allowing AI researchers and software engineers to iterate faster and explore new ideas. Responsibilities include collaborating with researchers, managing cloud environments, deploying and monitoring models, automating ML workflows with CI/CD, designing flexible ML workflows, enabling fast iteration with model tracking tools, optimizing model inference, and ensuring model reproducibility.
Must Have
- Strong Python programming skills
- Proficiency with DevOps/MLOps best practices (CI/CD, Git, Docker, IaC)
- Proficiency with AWS infrastructure (EC2, S3, SageMaker, Bedrock)
- Experience deploying ML models/LLMs in cloud and local environments
- Familiarity with distributed model training and optimization
- Ability to build effective ML pipelines
- Experience with ML model lifecycle tools (MLflow, DVC, Weights & Biases)
- Excellent problem-solving skills
- Fluent in English
Good to Have
- Proficiency in Java
- Experience with on-premise model deployment
- Experience setting up tools for model tracking, logging, and comparison
Perks & Benefits
- Pension Scheme: 1st Pillar (Unterstützungskasse)
- Pension Scheme: 2nd Pillar (bAV)
- 60% public transport reimbursement
- 28 PTO days + additional days based on seniority
- Generous discretionary Company Growth Bonus
- Global workforce with employees in 20+ countries
- Annual kick-off event
Job Description
What You Will Do Daily:
- Collaborate with AI researchers and engineers to bridge the gap between research and production.
- Manage research-friendly cloud environments that allow easy deployment and experimentation.
- 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).
- 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 Experience You Will Need:
- Technical background with a university degree in Computer Science, software engineering or a related field.
- Strong programming skills in Python. Proficiency in other languages such as Java is a plus.
- Proficiency with DevOps/MLOps best practices, including CI/CD, version control (Git), docker and IaC.
- Proficiency with AWS infrastructure, including EC2, S3, SageMaker and Bedrock.
- Experience deploying ML models and LLMs in cloud environments and local environments.
- Familiarity with distributed model training and model optimization.
- Ability to build effective ML pipelines for research and development.
- Experience with ML model lifecycle tools (e.g., MLflow, DVC, Weights & Biases).
- 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!).
- Great people make a great company. We value people skills as much as technical skills and strive to keep things friendly while still being passionate leaders in our domains.
- We have a flexible work policy that includes 3 days in-office and 2 days work-from-home each week for those located near our office locations; some locations such as Dubai, India, Japan and Australia operate fully remotely.
- We have a growth mindset. We love learning and believe continuous education is critical to our success. In an ever-changing industry, new skills are necessary, and we're happy to help our team acquire them.
- As the leader in our field, our products and services are as strong as our internal team members.
- We embrace transparency with regular meetings, cascading messages and updates on the growth and success of our organization.
Benefits of Working With Sonar:
- Pension Scheme: 1st Pillar (Unterstützungskasse): Automatic, financed by Sonar, 3% of gross salary.
- Pension Scheme:2nd Pillar (bAV): Voluntary, 15% contribution by Sonar from social security savings.
- Public transport reimbursement of 60% for annual subscription.
- We encourage usage of our robust time-off allocations with 28 PTO days for our employees based out of the Geneva region, plus additional days based on seniority and circumstances.
- Generous discretionary Company Growth Bonus, paid annually.
- Global workforce with employees in 20+ countries representing 35+ unique nationalities.
- We have an annual kick-off somewhere in the world where we meet to build relationships and goals for the company.