AI/ML Customer Engineer

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

Design and build production-grade AI/ML solution blueprints and reference codebases for enterprise customers in APAC. Package repeatable, open-source AI Quickstarts and co-develop/integrate architectures with partner teams. Drive benchmarking and evaluation with automated testing, telemetry, and ML performance metrics while ensuring regulated, secure, and privacy-conscious designs. Work hands-on across modern AI, MLOps, and cloud-native stacks with strong engineering autonomy.

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FursaFursa
Red Hat
Red Hat
2 days ago

AI/ML Customer Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 3 hours agoStatus: Live

Job Summary

Design and build production-grade AI/ML solution blueprints and reference codebases for enterprise customers in APAC. Package repeatable, open-source AI Quickstarts and co-develop/integrate architectures with partner teams. Drive benchmarking and evaluation with automated testing, telemetry, and ML performance metrics while ensuring regulated, secure, and privacy-conscious designs. Work hands-on across modern AI, MLOps, and cloud-native stacks with strong engineering autonomy.
Location: Singapore
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design and build production-ready architecture blueprints and reference codebases for enterprise-ready solutions, including scalability and network isolation boundaries.
  • •Package repeatable, extensible open-sourced AI Quickstarts to address real-world industry problems.
  • •Collaborate with external engineering teams (e.g., semiconductor partners, regional AI programs, software vendors) to validate joint blueprints and ensure stable integrations.
  • •Design and integrate automated testing, evaluation harnesses, and system telemetry to monitor latency, throughput, cost, and model quality.
  • •Incorporate robust data privacy, secure network perimeters, and localized hosting considerations to meet compliance and risk requirements.

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, TDD, CI/CD pipelines, and Git workflows.
  • •Hands-on proficiency in Python for ML and systems programming; familiarity with Go or C/C++ is preferred.
  • •Strong familiarity with PyTorch and NLP/vision ecosystems such as Hugging Face Transformers, datasets, and tokenizers.
  • •Practical experience deploying containerized applications with Kubernetes or production-grade enterprise container orchestration.
Experience:Enterprise AIOpen source
Education:Bachelor's in Computer Science, Computer Engineering, or a related quantitative field
Skills:Communication
Languages:English
Tech Stack:PythonGoC/C++PyTorchHugging Face TransformersDatasetsTokenizersKubernetesCI/CDGitRayMLflowKubeflowDoclingVector databasesLangChainLlamaIndexLangGraphAgentOpsModel Context Protocol

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