Staff Backline Engineer

Databricks Inc.; Singapore; On-site; SGD 180,000 - 300,000; Full time

Job summary

Databricks Inc. in Singapore seeks a Staff Backline Engineer to act as a technical SME for ML/AI platform areas, handling complex escalations and collaborating across Support, Engineering and Product teams.

You will diagnose and resolve high-impact issues, develop diagnostics, and mentor others to uplift the team’s troubleshooting capabilities. You will leverage deep knowledge of Python, Spark, MLflow and Model Serving to improve platform reliability, performance and customer outcomes on

Qualifications

• Deep troubleshooting of distributed ML/AI systems across code, frameworks, infra and the Databricks platform.
• Strong Python hands-on ability to build, modify and debug ML workloads with PyTorch, TensorFlow or Scikit-Learn.
• Knowledge of MLflow, Model Serving, Feature Engineering and Spark MLlib lifecycle management.
• Strong Spark knowledge: DataFrames, distributed execution, memory management and performance.

Responsibilities

• Serve as a senior escalation point for complex ML/AI issues including training, inference, and deployment.
• Perform deep investigations using logs, traces, metrics, profiling and configuration data to find root causes.
• Reproduce customer issues via hands-on experiments and workload construction in Python/Spark.
• Troubleshoot training/inference failures, performance degradation, memory/CPU/GPU issues and distributed execution problems.
• Collaborate with Engineering and Product to drive issue resolution and product improvements.
• Identify recurring failure patterns and build better diagnostics, tooling, automation and Claude skill capabilities.
• Mentor engineers and raise troubleshooting capabilities across the Support organization.
• Act as a technical SME for ML/AI platform areas in cross-functional initiatives with global impact.

Skills

Python

Spark

ML/AI systems

Model Serving

Troubleshooting

Cross-functional collaboration

Tools

MLflow

Spark MLlib

Kubernetes

CI/CD

Job description

About the Team

The Backline Engineering Team serves as the critical bridge between Frontline Support and Engineering. We handle complex technical issues and escalations across the Data and AI ecosystem.

With a strong focus on customer success, we are committed to delivering exceptional customer satisfaction by providing deep technical expertise, proactive issue resolution, and continuous platform improvements. We emphasise automation and tooling to enhance troubleshooting efficiency, reduce manual efforts, and improve the overall supportability of the platform and the health of our products.

By developing smart solutions and streamlining workflows, we drive operational excellence and ensure a delightful experience for both customers and internal teams.

As a Staff Backline Engineer, you will be a technical expert and escalation point for some of the most complex ML/AI issues. You will work across Support, Engineering, Product, and customers to troubleshoot difficult problems, reproduce issues, identify root causes, and drive them to resolution.

What You'll Do

• Serve as a senior escalation point for complex ML/AI issues involving model training, inference, Model Serving, MLflow, Feature Engineering, with knowledge of Spark, Delta Lake, and distributed workloads.

• Perform deep technical investigations using logs, traces, metrics, profiling, configuration, source code, and customer workloads to identify root cause.

• Reproduce customer issues through hands-on experimentation, Python/Spark development, workload construction, configuration changes, and performance analysis.

• Troubleshoot model training and inference failures, performance degradation, resource utilization, memory/CPU/GPU issues, distributed execution problems, and deployment/runtime failures.

• Partner closely with Engineering and Product teams to drive difficult issues to resolution and influence product improvements.

• Identify recurring failure patterns and turn them into better diagnostics, documentation, tooling, automation, and Claude skill capabilities.

• Mentor engineers and raise the technical troubleshooting capabilities of the broader Support organization.

• Act as a technical SME for ML/AI platform areas and contribute to cross-functional initiatives with global impact.

What We Look For

• Deep troubleshooting experience with distributed ML/AI systems and the ability to debug problems across application code, frameworks, infrastructure, and the Databricks platform.

• Strong hands-on Python experience and the ability to build, modify, and debug ML workloads using frameworks such as PyTorch, TensorFlow, or Scikit-Learn.

• Strong understanding of Databricks ML/AI technologies, including MLflow, Model Serving, Feature Engineering, Spark MLlib, and model lifecycle management.

• Strong Apache Spark knowledge, including DataFrames, query execution, distributed computing, memory management, shuffles, and performance optimisation.

• Experience troubleshooting training and inference performance, including CPU/GPU utilisation, memory issues, data bottlenecks, concurrency, latency, and distributed execution.

• Experience with ML deployment and infrastructure such as Kubernetes, cloud ML platforms, CI/CD, model monitoring, and production ML systems.

• Ability to read and reason about code, logs, stack traces, metrics, traces, execution plans, and system behaviour rather than relying solely on documentation or configuration recommendations.

• Demonstrated ability to independently own ambiguous, high-impact technical problems and drive them from symptom → investigation → root cause → resolution.

• Strong technical communication skills and the ability to influence Engineering, Product, Support, and customers.