MLOps Engineer

Python

MLOps Engineer

Python

al. Jerozolimskie 162A, Warszawa

deepsense.ai

Undetermined
B2B
Mid
Remote
4 439 - 8 324 USD
Net per month - B2B

Tech stack

    AWS

    regular

    GCP

    regular

    Azure

    regular

    Git

    regular

    GitFLow

    regular

    Docker

    regular

    Kubernetes

    regular

    SQL

    regular

    CI/CD

    regular

    Machine Learning

    junior

Job description

We focus on machine learning and big data for predictive modeling, computer vision, NLP/NLU, and reinforcement learning. 
We are looking for a professional - Machine Learning Ops Engineer (Mid/Senior) 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.

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,
  • holidays paid,
  • an attractive benefits package (subsidized medical care, sports, lunch card, frequent team-building events).
Published: 28.08.2022
Office location