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Offer summary
(Summary generated by AI based on the full job description)
The project involves a production ML recommendation platform built with AWS SageMaker, Python, MLflow, GitLab CI/CD. Key responsibilities include designing architecture, maintaining and optimizing MLOps pipelines, deploying and monitoring ML models, and collaborating with Data Scientists. The role covers scalable infrastructure development, CI/CD pipelines, model performance tracking, and mentoring engineers.
from: 20 July 2026
to: 19 August 2026
120 - 160 złnet (+ VAT)/ hr.B2B contract (full-time)
Offer parameters
level:senior • expert
working mode:remote
location:Warszawa, Masovian
Warszawa, Masovian
Requirements
Expected technologies
kubeflow
AWS SageMaker
SageMaker
MLflow
TensorFlow
PyTorch
Terraform
CloudFormation
Kubernetes
Docker
AWS
Our requirements
- 5+ years of professional experience as a Machine Learning Engineer, Senior MLOps Engineer, or in a similar role.
- Strong experience building and operating production Machine Learning systems.
- Hands-on experience with AWS SageMaker (training, deployment, endpoints, pipelines).
- Advanced Python programming skills.
- Strong knowledge of the complete MLOps lifecycle.
- Commercial experience with MLflow.
- Experience building CI/CD pipelines using GitLab CI/CD.
- Practical experience with at least one deep learning framework: TensorFlow PyTorch
- Experience deploying and maintaining ML models in cloud environments (AWS preferred).
- Solid understanding of Machine Learning model lifecycle, model serving, and monitoring.
- Ability to design scalable ML architectures and production-ready data pipelines.
- Experience mentoring engineers or providing technical guidance.
- Strong communication skills and the ability to work with cross-functional teams.
Optional
- Experience with recommender systems.
- Experience with model monitoring and observability tools such as Prometheus, Grafana, or Evidently AI.
- Docker and Kubernetes experience.
- Experience with Infrastructure as Code (Terraform or CloudFormation).
- MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
Your responsibilities
- Design and evolve the architecture of a large-scale production Machine Learning platform.
- Build, maintain, and optimize end-to-end MLOps pipelines.
- Deploy, monitor, and maintain machine learning models using AWS SageMaker.
- Develop and improve CI/CD pipelines for ML workflows using GitLab CI/CD.
- Manage experiment tracking, model versioning, and reproducibility with MLflow.
- Collaborate closely with Data Scientists to productionize machine learning models.
- Design scalable and reliable ML infrastructure following software engineering best practices.
- Implement monitoring, observability, and model performance tracking solutions.
- Write clean, maintainable, and well-tested Python code.
- Mentor engineers and Data Scientists on MLOps, software engineering, and production deployment best practices.
- Participate in architectural discussions and contribute to technical decision-making.
About the project
We are looking for an experienced Senior Machine Learning Engineer to join a global team responsible for a production-grade recommendation platform used across multiple international markets. The solution is already delivering significant business value and is entering its next stage of evolution, with a strong focus on scalability, reliability, and operational excellence.
This is a senior, hands-on engineering role where you will shape the architecture of a mature ML platform, strengthen the organization's MLOps capabilities, and work closely with Data Scientists to bring machine learning models into production.
The ideal candidate combines strong software engineering skills with deep expertise in Machine Learning Engineering and MLOps, particularly within the AWS ecosystem.
This is how we organize our work
This is how we work
at the client's site
SQUARE ONE RESOURCES sp. z o.o.
At Square One Poland we link IT experts with the business. With over 25 years of experience, we specialize in recruitment processes on a global scale. Despite years of experience, we still have a startup DNA and this is our advantage. Our offices are located in London and Warsaw, however, we can reach clients from all over the world, from start-ups to big worldwide corporations.
This is how we work
MLOps with AWS Sagemaker
120–160 zł / hr. (B2B)
I apply to:
SQUARE ONE RESOURCES sp. z o.o.
Warszawa, Masovian
Need more information?
- Make sure the body of the offer doesn’t already include what you’re looking for.
- Ask a question if you need more information you’re interested in.
- We’ll forward your question to the employer and aim to provide a response within 3 business days.