AI/ML Engineer

Red Hat
Singapore
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["Communication","Collaboration"]

Build production-ready enterprise AI/ML architecture blueprints and reference codebases, then package them as open-sourced AI Quickstarts. You’ll benchmark and evaluate models with automated testing and telemetry, incorporate security/privacy and regulated deployment requirements, and co-develop integrations with external engineering teams. Work in Red Hat’s Singapore AI Center of Excellence, delivering repeatable solutions across APAC without expectations of team management or deployment “last mile” work.

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FursaFursa
Red Hat
Red Hat
2 hours ago

AI/ML Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Build production-ready enterprise AI/ML architecture blueprints and reference codebases, then package them as open-sourced AI Quickstarts. You’ll benchmark and evaluate models with automated testing and telemetry, incorporate security/privacy and regulated deployment requirements, and co-develop integrations with external engineering teams. Work in Red Hat’s Singapore AI Center of Excellence, delivering repeatable solutions across APAC without expectations of team management or deployment “last mile” work.
Location: Singapore
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Design and build production-ready architecture blueprints and reference codebases for enterprise AI/ML workflows, including hardening, scalability, and network isolation boundaries.
  • •Package repeatable, extensible open-sourced AI Quickstarts to solve real-world industry problems and accelerate ecosystem adoption.
  • •Collaborate with external engineering teams to validate joint architecture blueprints and ensure stable integrations across the system stack.
  • •Design and integrate automated testing, evaluation harnesses, and system-level telemetry to monitor latency, throughput, cost, and model quality.
  • •Incorporate data privacy standards, secure network perimeters, and localized hosting considerations for regulated and secure deployments.

Key Requirements

  • •Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related quantitative field.
  • •Strong software engineering fundamentals, including clean code, test-driven development (TDD), CI/CD automation pipelines, and Git workflows.
  • •Hands-on proficiency in Python for machine learning and systems programming.
  • •Strong familiarity with PyTorch and core NLP/vision ecosystems such as Hugging Face Transformers, datasets, and tokenizers.
  • •Practical experience deploying containerized applications on Kubernetes and understanding model serving lifecycles and MLOps packaging.
Experience:Regulated industriesFinancial servicesPublic sectorHealthcareTelecommunications
Education:Bachelor's in Computer Science, Computer Engineering, or a related quantitative field
Skills:CommunicationCollaboration
Languages:English
Tech Stack:PythonGoC/C++GitTDDCI/CDPyTorchHugging Face TransformersDatasetsTokenizersKubernetesContainer orchestrationModel servingRayMLflowKubeflowDoclingVector databasesLangChainLlamaIndex

Company Brief

Red Hat
Provides enterprise open-source software solutions, including Red Hat Enterprise Linux, middleware, cloud, container, and Kubernetes technologies, delivering support, services, and solutions for hybrid cloud environments.
Industry: Enterprise Software
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Established Company
Valuation: Unicorn (USD 1B+)
Funding: IPO / Publicly Listed
Headquarters: Raleigh, United States
Founded: 1993
WebsiteLinkedIn