SalaryPeak

Machine Learning Software Engineer/Analyst

OPTIMUM SOLUTIONS (SINGAPORE) PTE LTD
Singapore 4+ years Posted Mar 12, 2026

Salary Range

SGD 60,000 - SGD 84,000 /year

SGD 5,000 - SGD 7,000/month

Skills Required

Machine LearningUNIX UtilitiesKubernetesUNIX scriptingAWSArtificial IntelligenceCore BankingAzure Machine LearningSystems IntegrationUnixPythonuser friendly toolsBankingFinanceDockerData ScienceGrafanaLarge Scale DeploymentsLinux

Job Description

Optimum Solutions (Registration Number: 199700895N) is Singapore's leading Information Technology , Consulting and Professional Services company with Competence in Digital Transformation, Automation, Robotics, Cloud, Big Data, Analytics and Emerging technologies projects. Optimum has been successfully delivering IT projects since 1997 and has been a key IT service provider to clients delivering Software Design, Development, Engineering and IT Transformation Projects.
Role: Machine Learning Software Engineer/Analyst

Key Technical Requirements:

  • Must : 4+ years of experience in Machine Learning engineering or AI system integration.
  • Working experience in Banking or Financial domain is required.
  • Develop and maintain automation scripts using Linux shell scripting, Python, or other relevant tools.
  • Experience with Observability framework, such as Langfuse, Elastic Stack, Grafana, OpenTelemetry.
  • Bash and Unix/Linux command-line toolkit is a must-have.
  • Hands-on experience with OpenShift, Docker, Kubernetes.
  • Ensure seamless deployment and integration between cloud/prem environments (AWS).
  • Knowledge of cloud platforms (e.g. AWS) is a must-have.
  • Exposure to data and network security and compliance in AI systems.
  • Knowledge of API integration and microservices architecture.
  • Proficiency in Python used both for automation and ML-related tasks
  • Knowledge of Workflow Orchestrator, such as Ctrl-M
  • Bachelor’s degree in Computer Science, Engineering, or a related field.
  • Good knowledge of Logging and Monitoring tools, such as Splunk and Geneos.
  • Understanding of Generative AI (e.g. prompt engineering, RAG pipelines) and Agentic AI concepts.
  • Domain : Banking