about the role
As a company working in the space of MLOps we are looking for an MLOps engineer to join our core team. A large part of our work lies in developing optimized architectures for model serving and monitoring. Your passion should be in helping us overcome the challenge of deploying them in the real world.
What you will be doing:
- Working as part of a cross-functional team of cloud engineers and machine learning engineers.
- Design, build and manage processes to deploy production models and monitor their quality and performance over time
- Develop and maintain the APIs serving our models.
- Building robust pipelines to automate the training of our models.
- Build next-gen features of our MLOps platform.
This is what we think you’ll need:
- Strong understanding and experience in designing and building APIs with Python (e.g. FastAPI).
- Experience with Docker and Kubernetes.
- Experience with building and maintaining CI/CD pipelines.
- Experience with cloud providers (e.g. AWS, GCP, Azure)
- Experience with using infrastructure as code (e.g. Terraform)
- Good understanding of SDLC principles
- A basic understanding of best MLOps practices, as well as machine learning and data science
Desired but not essential:
- Past interaction with ML frameworks like Keras or Pytorch.
- Past experience working with microservices architecture
- Past experience with ML platforms such as Kubeflow, Airflow.
- Past experience with Serving solutions like Seldon, Cortex.
- Absolute work title freedom
- Personal growth Fridays
- Team building trips
- Global AI events and conferences
- Coffee, tea, fruit and snacks
- Unlimited vacation days
- Competitive compensation