Python AI Engineer

Role & responsibilities

Technical & Behavioral Competencies

Must-have:

• >4 years of professional experience in Python Programming (OOP, decorators, code quality & security, performance optimization)
• Python environment building : strong uv skills, pip, mamba, micromamba,
• ML engineering: MLOps, model versioning, deployment.
• Containerization & orchestration: Docker, Kubernetes (scaling, resource management).
• CI/CD pipelines: Jenkins, GitLab CI/CD (advanced workflows, artifact management).
• Linux/Cloud infrastructure: Bash scripting, system administration, troubleshooting.
• Database systems: PostgreSQL (query optimization, schema design).
• Monitoring & incident management: Advanced logging & analysis, debugging complex issues.
• Denodo Platform Proficiency Ability to configure, query, and optimize virtual data layers using Denodos data virtualization tools, including creating logical views, data services, and API integrations.
• Strong SQL skills to write efficient queries in Denodo’s VQL (Virtual Query Language) and optimize data retrieval for AI model training and validation.
• Data Virtualization & Integration – Experience in connecting disparate data sources (e.g., databases, APIs, ETL pipelines) via Denodo to enable seamless data exploration for AI/ML workflows.
• Airflow DAG Development & Orchestration – Ability to design, implement, and maintain scalable Directed Acyclic Graphs (DAGs) for AI/ML pipelines, including task dependencies, retries, and dynamic workflow generation
• Airflow Integration & Optimization – Experience in:
• Connecting Airflow to data platforms (Denodo, PostgreSQL, S3, etc.) and ML tools (e.g., MLflow, Kubeflow) via hooks, custom operators, or APIs.
• Optimizing performance through parallelism tuning, executor selection (Celery/Kubernetes), and efficient XComs/artifact handling for large-scale workflows.

Nice-to-have:

• API design (Django framework).
• Distributed ML systems (Spark, Hadoop) and ETL/ELT pipelines (Airflow).
• Model compression/optimization (quantization, pruning).
• Data visualization (Kakfa, Kibana, ELK, Grafana) for monitoring dashboards.

Preferred candidate profile

Immediate Joiners