Machine Learning Ops Engineer

Warsaw/Bydgoszcz/Remote

deepsense.ai helps companies discover the potential of their data and use it to build competitive advantage in the most effective way. Our support covers all stages of the AI journey, from a feasibility study through to end‐to‐end AI solution development, deployment and maintenance. We follow methodology developed on the basis of research and commercial projects delivered for clients such as NTT, Nielsen, L’Oreal, Google and Intel.

We focus on machine learning and big data for predictive modeling, computer vision, NLP, and reinforcement learning. Our main technology stack is built around Python based on open-source packages and frameworks: scikit-learn, LightGBM, OpenCV, PyTorch and TensorFlow. If you are open-minded and eager to continuously develop yourself, our company is the place for you.
We are looking for a professional to help us deliver Machine Learning (ML) solutions into production.

You’ll be responsible for:

  • creating and controlling ML pipelines in production environments (including cloud),
  • helping DataScientists and Engineers design the architecture of ML solutions to meet
  • functional and performance requirements,
  • controlling ML solution CI/CD pipelines,
  • design and introduction of code / ML models / datasets versioning,
  • monitoring production ML solutions.

The successful applicant will have knowledge of:

  • at least one public cloud provider architecture and services – preferably AWS (and/or GCP/Azure),
  • GIT, GitFlow,
  • basics of Machine Learning (including Deep Learning) – you should understand the problems specific to machine learning,
  • SQL/NoSQL Databases,
  • containerization (Docker and Kubernetes).

We also welcome:

  • experience in supporting teams in ML Projects in an MLOps/DevOps role,
  • programming skills in Python,
  • knowledge of the pros and cons of cloud providers’ services for ML and terraform
    Terraform.

We offer:

  • a chance to work on both commercial and research-oriented machine learning projects,
  • an opportunity to master deep learning, NLP and classical machine learning under the guidance of experts,
  • an opportunity to participate in Tech Talks (internal training and seminar sessions),
  • flexible working hours,
  • an attractive benefits package (subsidized medical care, sports, frequent team-building events, fun room).