MLOps for ML pipelines

Andersen; United States; Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote or hybrid work option

Private health insurance

Career growth and mentoring

Certification compensation (AWS, PMP)

Referral program

Training portal access

Job summary

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

You design AWS architecture, build GitLab CI/CD pipelines, implement Terraform IaC, and containerize services for multi-environment deployments. Remote or hybrid work options available.

Qualifications

• 5+ years in DevOps / Cloud with AWS as primary platform.
• Hands-on 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 with GitLab CI or GitHub Actions.
• Docker/container deployment on AWS (ECS/EKS/Lambda) and S3/RDS in prod.
• Multi-environment infra (dev, pre-prod, prod); English at least Intermediate+.

Responsibilities

• Design and set up AWS architecture for ML pipeline (ingestion, inference, storage).
• Build CI/CD pipelines in GitLab for app and model components.
• Implement IaC with Terraform; set up dev, pre-prod, prod targets.
• Automate provisioning and teardown of environments; containerize services.
• Integrate S3 and RDS; monitor pipelines, logs, and tracing.
• Document infrastructure and deployment for knowledge transfer.

Skills

AWS cloud

MLOps

Python

CI/CD pipelines

Terraform

Docker

SageMaker

GitLab CI

ECS/EKS/Lambda

S3/RDS

Hybrid cloud & on-prem

English (Intermediate+)

Tools

Terraform

GitLab CI

Docker

SageMaker

AWS CLI

Kubernetes

Job description

Описание:

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.

Задачи:

• 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.

Требования:

• 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.
• Будет плюсом: 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.

Условия:

• 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.
• Bright corporate life (parties / pizza days / PlayStation / fruits / coffee / snacks / movies).
• Certification compensation (AWS, PMP, etc).
• Referral program.
• Private health insurance and sports compensation, depending on the type of employment.