MLOps Engineer
DevOps
MLOps Engineer
Kraków
Type of work
Undetermined
Experience
Mid
Employment Type
B2B
Operating mode
Remote
Tech stack
AWS
GCP
Azure
Git
GitFLow
Docker
Kubernetes
SQL
CI/CD
Machine Learning
Job description
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 - 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).
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