About the Job:
Greetings! We currently have an urgent opening for an MLOps Engineer with more than 6 years of experience at Synechron in Riyadh, KSA. As an MLOps Engineer, you will be responsible for designing, deploying, and maintaining robust machine learning systems. You will bridge the gap between data science and DevOps to ensure efficient model deployment, monitoring, and scalability in production.
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Key Responsibilities:
- ML Pipeline Development: Build and maintain end-to-end pipelines for training, validation, and deployment.
- CI/CD Automation: Implement CI/CD workflows for ML models using tools like Jenkins, GitLab, or GitHub Actions.
- Cloud & Infrastructure: Manage cloud-based ML infrastructure (AWS/GCP/Azure), optimizing cost and performance.
- Containerization & Orchestration: Deploy models using Docker/Kubernetes and orchestrate workflows with Airflow/Kubeflow.
- Monitoring & Alerting: Track model performance, data drift, and system health with Prometheus/Grafana/Evidently.
- Collaboration: Work with data scientists to operationalize models and collaborate with DevOps teams to ensure system reliability.
- Security & Compliance: Ensure adherence to GDPR/CCPA and implement model governance/auditability.
- Model Retraining: Design automated retraining pipelines and version control (DVC, MLflow).
- Innovation: Stay updated on MLOps trends (e.g., serverless, feature stores) and drive best practices.
Technical Expertise:
- Proficient in Python, TensorFlow/PyTorch, and cloud platforms (AWS/GCP/Azure).
- Experience with Docker/Kubernetes, CI/CD tools, and Infrastructure as Code (Terraform/CloudFormation).
- Knowledge of data engineering tools (Spark/Kafka) and monitoring frameworks.
- Deep understanding of model development, deployment, and scalability.
Education:
- Bachelor’s/Master’s in Computer Science, Data Science, or related field.
Experience:
- 5+ years in MLOps/DevOps/Data Engineering roles with a proven track record of production deployment.
Preferred Qualifications:
- Certifications in cloud (AWS ML, GCP ML Engineer) or ML frameworks.
- Experience with feature stores (Feast), model registries, and big data technologies (Hadoop).
- Experience with SQL & NoSQL databases (Mongo, PostgreSQL).
- Contributions to open-source MLOps tools or publications in ML deployment.
If you are interested in this opportunity, kindly send your updated profile along with details including total experience, experience in MLOps, and current notice period.
Work Conditions: On-site, Full-time
Language Requirements: Not specified.
