AI/ML Ops - Senior Engineer

Job Description

We are looking for a skilled AI/ML Ops Engineer to join our team to bridge the gap between data science and production systems. You will be responsible for deploying, monitoring, and maintaining machine learning models and data pipelines at scale. This role involves close collaboration with data scientists, engineers, and DevOps to ensure that ML solutions are robust, scalable, and reliable.

Key Responsibilities:

• Design and implement ML pipelines for model training, validation, testing, and deployment.
• Automate ML workflows using tools such as MLflow, Kubeflow, Airflow, or similar.
• Deploy machine learning models to production environments (cloud).
• Monitor model performance, drift, and data quality in production.
• Collaborate with data scientists to improve model robustness and deployment readiness.
• Ensure CI/CD practices for ML models using tools like Jenkins, GitHub Actions, or GitLab CI.
• Optimize compute resources and manage model versioning, reproducibility, and rollback strategies.
• Work with cloud platforms AWS and containerization tools like Kubernetes (AKS).
• Ensure compliance with data privacy and security standards (e.g., GDPR, HIPAA).

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 5+ years of experience in DevOps, Data Engineering, or ML Engineering roles.
• Strong programming skills in Python; familiarity with R, Scala, or Java is a plus.
• Experience with automating ML workflows using tools such as MLflow, Kubeflow, Airflow, or similar
• Experience with ML frameworks like TensorFlow, PyTorch, Scikit-learn, or XGBoost.
• Experience with ML model monitoring and alerting frameworks (e.g., Evidently, Prometheus, Grafana).
• Familiarity with data orchestration and ETL/ELT tools (Airflow, dbt, Prefect).

Preferred Qualifications:

• Experience with large-scale data systems (Spark, Hadoop).
• Knowledge of feature stores (Feast, Tecton).
• Experience with streaming data (Kafka, Flink).
• Experience working in regulated environments (finance, healthcare, etc.).
• Certifications in cloud platforms or ML tools.

Soft Skills:

• Strong problem-solving and debugging skills.
• Excellent communication and collaboration with cross-functional teams.
• Adaptable and eager to learn new technologies.

Mandatory Competencies