KEY RESPONSIBILITIES

ML Data Platform Engineering & Administration

• Install, configure, and maintain ML data platforms on top of Kubernetes, Object Storage, Cassandra, Postgres and related technologies
• Monitor platform performance and optimize as needed for reliability and efficiency

Platform Configuration and Maintenance

• Implement and manage platform configurations, ensuring adherence to best practices and security standards
• Regularly update and patch systems to maintain security and stability

Collaborate with Cross-Functional Teams

• Work closely with ML and data engineers and other roles to align IT needs and strategies
• Provide expert guidance on ML data platform best practices and optimization

Troubleshoot and Resolve Technical Issues

• Identify, diagnose, and resolve data platform problems in a timely manner
• Escalate complex issues to upper-level support when necessary

Backup and Recovery Management

• Implement and maintain backup and recovery strategies for data platforms, ensuring data integrity and availability

Maintain and Update Documentation

• Create and maintain documentation related to data platform administration, configuration, and maintenance
• Share knowledge with team members and contribute to a culture of continuous learning

Enhance Data Security and Compliance

• Ensure data platforms adhere to security best practices and comply with relevant regulations
• Stay up-to-date on industry trends and evolving security standards

Drive Continuous Improvement

• Evaluate and implement new technologies and techniques to enhance data platform performance and administration
• Proactively identify areas for improvement, prepare plan for implementation and get support from management and development teams
• Always prefer automation and code-first approach over hard to reproduce manual tasks

REQUIREMENTS

• A degree in computer science, software engineering, information technology or related fields is preferred
• Production use experience with AI agents (like Langchain, Agno) and LLM stack (like KServe, vLLM, pgvector)
• At least 3 years of experience in data platform (Kafka, Spark, Airflow, Flink, KServe, MLFlow, Lakekeeper) and related infrastructure installation, administration, patching and automation (Linux, Ansible, Helm, Terraform, Kubernetes, Ceph)
• Continuous improvement mindset covering daily operations, stability, reliability and performance of ML data platforms
• Knowledge of key concepts like infrastructure-as-code, templates, playbooks, code versioning using GIT, CI/CD automation, high availability, disaster and recovery
• Proficient in Linux Shell, Python scripting, configuration using JSON, YAML files
• Ability to troubleshoot infrastructure, analyze logs and setup/update monitoring dashboards and metrics, describe and document root cause, attend retrospective meetings
• Understand IT systems documentation, data flow diagrams, integration diagrams and related terminology (UML)
• Understand major ML data platforms concepts – LLM, RAG, agent, quantization, fine-tuning, Data Lake, ACID, Distributed Query, Feature Store, Data Governance, Data Catalogue, Streaming, Batch , Parquet
• Proficient in using documentation (Markdown, Visio, Office 365) and communication tools (MS Teams)
• Proficient user of change management and support ticket/service desk tools (JIRA SD)

COMPENSATION & BENEFITS

• 13th Salary Fixed and KPI Bonus
• Premium Health Care program
• 24/7 Accidental Insurance
• 100% Social Insurance
• Meal + Phone Allowance
• 15 Annual Leaves
• Yearly Medical Checkup
• Professional and Transparent Working Environment
• Apply Latest Financial Technology in the World