MLOps Lead / ML Platform Engineer
Our client builds an AI product for creative professionals, and machine learning is at the core of it. They need an MLOps Lead who connects the ML researchers with the software engineers. You will take ownership of the ML infrastructure, make the daily work of the ML teams easier, and make sure that new models and features get to production without problems.
The work is hands-on. You will design, build and operate the pipelines, the tooling and the processes that the ML teams use to train, test, release and monitor their models.
Responsibilities
- Take ownership of the ML infrastructure and the CI/CD pipelines, and keep improving them
- Watch the production systems, investigate incidents, and make alerting and automation better
- Control how models and ML features are released from one environment to the next
- Keep the code quality high, the systems reliable and the architecture ready to scale
- Create and support internal tools that make ML development faster
- Help with releases
find the risks early and make delivery more efficient
- Look after the core infrastructure and the internal platforms that are already in place
Requirements
- At least 5 years of work in MLOps, DevOps, backend engineering or a related field
- Very good Python
- Practical experience with CI/CD, Docker and a public cloud, ideally AWS
- Good knowledge of how ML models are developed, released and operated
- A strong problem solver with solid system design skills
- A plus: Kubernetes, PyTorch or TensorFlow, data pipelines, model versioning
What will be your next steps?
Quick non-technical conversation
Our initial conversation is a brief, non-technical discussion to understand your background and career aspirations. We're keen to learn about your communication style and how you approach teamwork and decision-making.
60 to 90 minutes technical interview
This in-depth technical assessment, lasting 60 to 90 minutes, is designed to evaluate your specific skills and expertise. We will present you with challenges relevant to our client’s requirements.
Client interview
In this stage, you will meet directly with the client for a final technical discussion. This interview will be similar in format to our internal technical assessment, allowing the client to see firsthand how your expertise aligns with their specific project needs and team.
Offer
Congratulations on successfully completing our evaluation process. We are pleased to extend an offer and recommend you to our clients.
Apply for this role
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