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

Responsibilities:

• Optimize, standardize and implement data science and machine learning solutions at scale and in cloud-based environments (Azure)

• Participate in the end-to-end lifecycle of data science projects through the use of DevOps, code, experiment and model management, CI/CD and further industry best practices

• Write well-designed, testable, efficient code

• Work closely with engineering to continuously improve the way we consume data and deploy models in production

• Design and lead on monitoring, troubleshooting, debugging and incident management for our ML pipelines

• Be a trusted advisor and evangelist to the team and stakeholders on various aspects of ML Ops, from scaling and throughput, to infrastructure and deployment strategies

Requirements:

• 2+ years of professional experience in ML Ops or ML engineering, particularly in productionizing and scaling ML models

• Business-ready command of English, written and spoken

• Broad familiarity with Azure cloud environment and Databricks, including its setup and maintenance as an ML platform

• Proven experience with software development best practices including testing, continuous integration, and DevOps tools

• Good understanding of data science lifecycle and the way data scientists work to deliver value

• Advanced proficiency with Python and SQL in version control systems (git) plus their use in building ML & data pipelines

• Familiarity with agile software development lifecycle (SCRUM, Kanban, etc.)

• Attention to clarity of code, ease of development, and correctness of implementations

Nice to have: 

• Experience in productionizing ML tools involving a user interface, e.g. Dash, Shiny R, Streamlit

• Great communication skills to guide audiences of a broad technical knowledge range through complex ML Ops topics

• Practice in coaching / mentoring younger team members in your expertise areas

• Knowledge of KNIME and tools based on it

Offer:

• Private medical care

• Co-financing for the sports card

• Constant support of dedicated consultant

• Employee referral program