We are looking for an experienced Lead MLOps Engineer to make our team even stronger.

The ideal candidate will combine deep knowledge of machine learning operations with a pragmatic approach to operational excellence, delivering robust, scalable, and efficient solutions for deploying and managing ML pipelines and models across our diverse project stack.

Technologies

• Python, LLM
• Predictions, Large data, Spark
• GCP Cube flow pipelines (optional)
• Vertex AI
• Databricks

Responsibilities

• Design and manage MLOps pipelines ensuring standardization, scalability, and real-time monitoring
• Implement continuous integration and continuous deployment (CI/CD) pipelines alongside incident response procedures
• Optimize model performance and manage lifecycle from development to deployment
• Lead the strategy for model scalability across Python and other predictive analytics environments
• Coordinate with data science teams to ensure that models are efficiently integrated and maintained in production systems

Requirements

• Minimum 3 years of experience in MLOps or ML engineering roles
• Expertise in Databricks and Azure cloud platforms
• Proficiency in MLOps tooling and monitoring tools
• Background in implementing CI/CD frameworks such as Jenkins, Concourse, or GitLab CI/CD
• Excellent communication skills and capacity to collaborate effectively with diverse teams
• Understanding of Python, LLM, and large data processing frameworks like Spark
• Qualifications in GCP Cube flow pipelines, Vertex AI, or familiarity with these technologies

We offer

• Opportunity to work in a fast-paced, agile, software engineering culture
• Benefit program (5 weeks of vacation, 5 paid sick days, meal vouchers, cafeteria and recreation bonuses, reimbursement of glasses, contribution to pension fund)
• Referral bonuses for recommended candidates
• English language courses
• Great learning and development opportunities, including in-house professional training, career advisory and coaching, sponsored professional certifications, well-being programs, LinkedIn Learning Solutions and much more

Certain benefits and perks may be subject to eligibility requirements and may be available only after you have passed your probationary period.