MLOps Support Engineer
4 weeks ago
At TecQubes Technologies, we are seeking a highly skilled MLOps Support Engineer to join our team. As an MLOps Support Engineer, you will play a crucial role in ensuring the reliability, performance, and scalability of machine learning operations within our organization.
Key Responsibilities:
- Technical Support: Serve as the first point of contact for technical issues related to machine learning infrastructure pipelines and deployments.
- Incident Management: Monitor system health and performance metrics to proactively identify and address potential issues before they impact operations.
- Documentation and Knowledge Sharing: Maintain comprehensive documentation of support procedures, troubleshooting guides, and best practices to facilitate knowledge sharing and training.
- Process Optimization: Identify opportunities to streamline and automate support processes, workflows, and tooling to improve efficiency and scalability.
- Training and Education: Provide training and guidance to users, developers, and stakeholders on MLOps best practices, tools, and workflows.
Requirements:
- 5 to 8 years of experience with a bachelor's degree in computer science, engineering, or a related field.
- Proven experience in a technical support or operations role, preferably in a data-driven or machine learning environment.
- Strong understanding of machine learning concepts, algorithms, and workflows.
- Proficiency in scripting and automation using languages such as Python.
- Experience with containerization technologies (Docker, Kubernetes), SQL, Airflow, Azure Databricks, APIs, Arize AI, DataDog, version control system (Git), Azure cloud Compute Services, Storage Services, Networking Services, Identity Access Management, Security & Compliance.
- Excellent analytical and problem-solving skills with the ability to troubleshoot complex technical issues and perform root cause analysis.
- Strong communication and interpersonal skills with the ability to collaborate effectively with diverse teams and stakeholders.
- Self-motivated and proactive attitude with a commitment to continuous learning and professional development.
Preferred:
- Azure Certifications: Azure AI Engineer Associate, Azure Data Scientist Associate.
- Experience with MLOps tools and frameworks (e.g., MLflow, TensorFlow Extended).
- Experience with ML algorithms, Data Preparation, model monitoring (Data drift & Model performance) and retraining.
- Knowledge of data engineering concepts and tools for data preprocessing and feature engineering.
- Familiarity with DevOps practices and configuration management.
- Understanding of security best practices for machine learning systems and data privacy regulations.
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