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MLOps Engineer

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MidHybryda·WarszawaFull-time

#369547·Dodano 4 miesiące temu·9

Źródło: nofluffjobs.com

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Tech Stack / Keywords

PythonMLOpsMachine learning MLflowCloud platformAzure MLAzure DevOpsAWS EC2AWS S3IAMNetworkingGCPCD pipelinesGitHub Actions GitLab CIInfrastructure as CodeTerraform Docker KubernetesAmazon EKSECSAWS ECSData managementSQL PostgreSQL PySpark Databricks Big DataSecurityVirtual private networkDegree

Podsumowanie oferty

The MLOps Engineer will design, develop, and maintain end-to-end machine learning pipelines, automate infrastructure for model training and inference in cloud environments, and implement CI/CD/CT practices for code, data, and ML models. The role involves ensuring the reliability, scalability, and security of AI services in production and collaborating closely with Data Scientists and DevOps Engineers to transform prototypes into production-ready solutions. The position requires strong proficiency in Python, MLOps experience, and expertise with cloud platforms and containerization technologies.

Wymagania

Strong proficiency in Python, including production-grade development and experience with ML and automation libraries
2+ years of MLOps experience deploying, operating, and maintaining machine learning models in production
Understanding of the ML model lifecycle, machine learning algorithms, feature engineering, and model monitoring (drift detection, performance tracking)
Experience with data and experiment versioning tools such as MLflow, DVC, and Weights & Biases
Hands-on experience with cloud platforms: Azure ML, Azure DevOps Pipelines, ACR; AWS EC2, S3, IAM, Networking; GCP
Experience building and maintaining CI/CD pipelines (GitHub Actions, Azure DevOps, GitLab CI)
Understanding of Infrastructure as Code principles and tools such as Terraform
Experience with Docker and container orchestration technologies (Kubernetes, Amazon EKS, ECS)
Strong SQL skills (MS SQL, PostgreSQL), including writing complex queries and data manipulation
English proficiency at B2 level or higher

Nice to have:

Experience with LLM- and Generative AI-based solutions in production
Experience with PySpark, Databricks, and Big Data technologies
Understanding of networking concepts, security configurations, and virtual private networks
Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, or related field

Obowiązki

Design, develop, and maintain end-to-end ML pipelines (data → training → deployment → monitoring)
Automate infrastructure for model training and inference workloads in cloud environments
Implement CI/CD/CT practices for code, data, and machine learning models
Ensure the reliability, scalability, and security of AI services in production
Collaborate closely with Data Scientists and DevOps Engineers to transform prototypes into production-ready solutions

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