Description

You will lead the company's machine learning strategy by building robust infrastructure and ensuring regulatory compliance. Your day-to-day involves scaling GenAI agents and empowering teams through ML-as-a-Service.

Requirements

• •4+ years experience in MLOps, ML engineering, or applied machine learning
• •Strong ownership mentality and impact orientation
• •Clear communication of complex ML concepts
• •Experience with cloud infrastructure, container orchestration, and IaC
• •Track record with ML lifecycle tooling
• •Familiarity with MLFlow, Airflow, or similar platforms
• •Strong Python programming and ML framework skills
• •Experience with Snowflake, Databricks, or modern data stacks
• •Exposure to GenAI applications
• •Experience operationalizing AI regulatory frameworks
• •Experience enabling AutoML or self-serve ML platforms
• •Enthusiasm for Data Engineering and AI innovation
• •Collaborative, pragmatic, and cross-functional teamwork
• •Curious and proactive learning of GenAI

Tasks

• •Act as the company's AI Act Steward
• •Ensure compliance with the EU AI Act
• •Build a central registry for models
• •Monitor high-risk models for fairness
• •Design a centralized Model Registry
• •Implement a scalable Feature Store
• •Automate monitoring for GenAI models
• •Build Airflow-based orchestration pipelines
• •Collaborate on CI/CD for ML workflows
• •Develop GenAI agents for data querying
• •Deploy agentic LLM workflows using Snowflake
• •Provide ML-as-a-Service capabilities to teams
• •Evaluate and enable ML and GenAI PoCs
• •Champion AutoML and reusable experimentation tools
• •Identify and implement high-impact use cases

Tools & Technologies

Benefits