MLOps / Cloud Engineer (AWS)

Andersen Inc.; Warszawa; Hybrid; PLN 200,000 - 280,000; Full time

Benefits offered by this job

Private health insurance

Sports compensation

Referral program

Corporate training portal

Job summary

Andersen Lab is hiring an MLOps / Cloud Engineer (AWS) to design and operate an ML-powered image analysis platform for automated defect detection in industrial quality control. You will build the AWS-based ML pipeline, containerize services, and implement IaC and CI/CD practices to enable robust, scalable deployments.

The role requires 5+ years in DevOps/Cloud with AWS, hands-on ML/Python deployment on AWS (SageMaker), and experience with MLOps tooling.

Qualifications

• 5+ years of experience in DevOps/Cloud with AWS as the primary platform.
• Hands-on experience deploying ML models or Python services on AWS (SageMaker, endpoints, Step Functions).
• Experience with MLOps tooling (MLflow or similar).
• Terraform in real‑world projects.
• CI/CD pipelines with GitLab CI (GitHub Actions acceptable).
• Docker and container deployments on AWS (ECS/EKS/Lambda).
• Experience with S3 and RDS in production environments.
• Managing multi‑environment infra (dev, pre-prod, prod).
• English level: Intermediate+ or higher.

Responsibilities

• Design and set up AWS architecture for the ML pipeline (ingestion, inference, storage).
• Build CI/CD pipelines in GitLab for application and model components.
• Implement Infrastructure as Code with Terraform.
• Set up multi-environment deployment targets (dev/pre-prod/prod).
• Automate provisioning and teardown of environments.
• Containerize services and integrate AWS storage/services.
• Set up pipeline monitoring, logging, and traceability.
• Document infrastructure and deployment for knowledge transfer.

Skills

AWS

DevOps

MLOps

Terraform

GitLab CI

Docker

SageMaker

ECS/EKS/Lambda

S3/RDS

English Proficiency

Tools

Terraform

GitLab CI

Docker

SageMaker

Job description

Andersen is hiring an MLOps / Cloud Engineer (AWS) for a project developing an ML-powered image analysis platform to automate defect detection and improve industrial quality control.

Our customer is an international company providing specialized industrial materials and technology solutions to businesses across multiple sectors. Combining technical expertise with research and development capabilities, the organization helps customers improve manufacturing processes, enhance product quality, and increase operational efficiency. Its activities focus on delivering innovative solutions, supporting sustainable industrial practices, and adapting to evolving technological and market requirements.

The project is focused on developing and enhancing an image analysis platform for quality control in electroplating and surface finishing processes. It leverages Machine Learning and Computer Vision to automate defect detection, image segmentation, feature measurement, and comparison with expert reference values, enabling accurate, consistent, and objective quality assessments.

Responsibilities

• Design and set up AWS architecture for the ML pipeline: image ingestion, inference, storage of images, metadata and results.
• Build CI/CD pipelines in GitLab for application and model components.
• Implement Infrastructure as Code with Terraform.
• Set up development, pre-production and production deployment targets.
• Automate provisioning and controlled teardown of test and pre-production environments.
• Containerize services and integrate S3 and RDS.
• Set up pipeline monitoring, logging and operational traceability.
• Document infrastructure and deployment for knowledge transfer.

Requirements

• Experience in DevOps / Cloud for 5+ years, with AWS as the primary cloud platform.
• Hands‑on experience deploying ML models or Python services on AWS, including SageMaker, inference endpoints, and Step Functions.
• Experience with MLOps tooling, including MLflow or similar solutions.
• Hands‑on experience using Terraform in real‑world projects.
• Experience building and managing CI/CD pipelines using GitLab CI (GitHub Actions is also acceptable).
• Experience with Docker and container deployment on AWS, including ECS, EKS, or Lambda.
• Experience working with S3 and RDS in delivered environments.
• Experience setting up and managing multi‑environment infrastructure, including dev, pre-prod, and prod.
• Level of English – from Intermediate+ and above.

Desired skills

• Experience building infrastructure from scratch for new products.
• Experience working with hybrid on‑premise and cloud environments.
• Knowledge of security and compliance practices, including ISO 27001 or similar standards.
• Experience working with GPU instances and managing cloud costs.
• Experience in teamwork with leaders in FinTech, Healthcare, Retail, Telecom, and others. Andersen cooperates with such businesses as Samsung, Siemens, Johnson & Johnson, BNP Paribas, Ryanair, Mercedes, TUI, Verivox, Allianz, T-Systems, etc..
• The opportunity to change the project and/or develop expertise in an interesting business domain.
• Job conditions – you can work both fully remotely and from the office or can choose a hybrid variant.
• Guarantee of professional, financial, and career growth! The company has introduced systems of mentoring and adaptation for each new employee.
• The opportunity to earn up to an additional 1,000 EUR per month, depending on the level of expertise, which will be included in the annual bonus, by participating in the company's activities.
• Access to the corporate training portal, where the entire knowledge base of the company is collected and which is constantly updated.
• Referral program.
• Private health insurance and sports compensation, depending on the type of employment.