19 hours ago

SENIOR SOFTWARE ENGINEER (Guangzhou, GD, CN, 510620)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Build and operate core MLOps platform capabilities across GCP and on-prem Kubernetes, including standardized CI/CD patterns for ML training, packaging, deployment, and rollback. Engineer and support ML workflow orchestration with Airflow, manage experiment tracking and model registry with MLflow, and enable batch and near-real-time scoring patterns. Drive observability, reliability, incident response improvements, and secure-by-design controls for releases and operations.

Location: Guangzhou

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Design, build, and operate core MLOps platform capabilities across GCP and on-prem Kubernetes (multi-environment, multi-tenant where required).
•Create reusable CI/CD patterns for ML workloads, including reference implementations and templates for training, deployment, promotion, and rollback.
•Engineer and support ML pipeline orchestration using Airflow, including DAG standards, scheduling, retries, backfills, and operational runbooks.
•Operate and extend MLflow for experiment tracking and model registry, including artifact storage, environment promotion, access controls, and retention.
•Implement observability and reliability (monitoring, alerting, dashboards, logging, tracing) and embed secure-by-design practices (IAM/RBAC, secrets management, encryption, vulnerability scanning, audit trails).

Key Requirements

•Strong software engineering skills, typically Python and Flask (plus one of Java/Go/Scala/Shell), with testing, code review, and maintainable design.
•Hands-on experience building MLOps platforms or shared ML enablement tooling beyond single-model deployments.
•Strong Kubernetes experience including deployments, services/ingress, configmaps/secrets, autoscaling, and troubleshooting.
•Experience with GCP services relevant to ML platforms such as GCS, IAM, networking, and logging/monitoring (plus GKE/Cloud Build where used).
•Proven experience operating MLflow (tracking + registry) and building/operating Airflow pipelines in production, including CI/CD for containerised workloads and operational observability and security practices.

Skills:TestingCode reviewMaintainable designIncident managementRoot cause analysisSecure engineering mindset

Tech Stack:PythonFlaskJavaGoScalaShellKubernetesGCPGCSIAMAirflowMLflowCI/CDKubernetes ingressGKECloud BuildRBACSecrets managementEncryptionVulnerability scanning

Company Brief

HSBC

Global banking and financial services organisation offering retail, commercial, corporate and investment banking, wealth management, and global markets services across Europe, Asia, the Americas and the Middle East.

Industry: Banking

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: London, United Kingdom

Founded: 1865

Glassdoor: 3.6

Website LinkedIn

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HSBC

19 hours ago

SENIOR SOFTWARE ENGINEER (Guangzhou, GD, CN, 510620)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Location: Guangzhou

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Design, build, and operate core MLOps platform capabilities across GCP and on-prem Kubernetes (multi-environment, multi-tenant where required).
•Create reusable CI/CD patterns for ML workloads, including reference implementations and templates for training, deployment, promotion, and rollback.
•Engineer and support ML pipeline orchestration using Airflow, including DAG standards, scheduling, retries, backfills, and operational runbooks.
•Operate and extend MLflow for experiment tracking and model registry, including artifact storage, environment promotion, access controls, and retention.
•Implement observability and reliability (monitoring, alerting, dashboards, logging, tracing) and embed secure-by-design practices (IAM/RBAC, secrets management, encryption, vulnerability scanning, audit trails).

Key Requirements

•Strong software engineering skills, typically Python and Flask (plus one of Java/Go/Scala/Shell), with testing, code review, and maintainable design.
•Hands-on experience building MLOps platforms or shared ML enablement tooling beyond single-model deployments.
•Strong Kubernetes experience including deployments, services/ingress, configmaps/secrets, autoscaling, and troubleshooting.
•Experience with GCP services relevant to ML platforms such as GCS, IAM, networking, and logging/monitoring (plus GKE/Cloud Build where used).
•Proven experience operating MLflow (tracking + registry) and building/operating Airflow pipelines in production, including CI/CD for containerised workloads and operational observability and security practices.

Skills:TestingCode reviewMaintainable designIncident managementRoot cause analysisSecure engineering mindset

Tech Stack:PythonFlaskJavaGoScalaShellKubernetesGCPGCSIAMAirflowMLflowCI/CDKubernetes ingressGKECloud BuildRBACSecrets managementEncryptionVulnerability scanning

Company Brief

HSBC

Industry: Banking

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: London, United Kingdom

Founded: 1865

Glassdoor: 3.6

Website LinkedIn