MLOps Engineer

As a recruitment company, DCG understands that every business is powered by experienced professionals. Our management style and partnership approach enable us to meet your needs and provide continuous support. Due to our ongoing growth and the large number of recruitment projects we undertake for our partners, we are currently looking for MLOps Engineer

Hybrid work: 3 days per week in the office

Responsibilities:

• Collaborate with Data Scientists, MLOps engineers and business stakeholders to understand requirements and translate them into scalable data and ML solutions

• Design, build and maintain robust data pipelines for ML model training and inference using structured and unstructured data of various scale

• Develop and maintain production-ready code for training, serving, and monitoring machine learning models

• Implement CI/CD pipelines deployment and retraining workflows

• Ensure reproducibility and traceability of ML experiments using versioning and metadata tools

• Monitor performance and health of deployed models

Requirements:

• Fluent in Python

• Familiarity with software engineering principles, including unit testing and version control (e.g., Git)

• Familiarity with Linux-based environments and scripting for automation

• Experience monitoring ML models in production, including logging, metrics, and alerting

• Experience in working with Kubernetes

• Experience with Microsoft Azure; nice to have experience deploying ML solutions in cloud environments (e.g., Microsoft Azure, AWS, or GCP)

• Minimum of 3 years of experience in a data science, data engineering, ML engineering or MLOps engineering role

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Engineering, or a related field

• Knowledge and experience with Vector DBs

• Understanding and experience in working with CI/CD tools

• Understanding and experience in working with CI/CD tools

• Knowledge of machine learning techniques and model lifecycle management

• Knowledge of methods and techniques for explaining decisions of ML models

Offer:

• Private medical care (dental care + vision care plan)

• Life insurance

• Sports card

• Training & learning opportunities

• Language course co-financing

• Annual bonus

• Employee referral program