AI/ML Engineer

About the Singapore AI Center of Excellence (COE)

The Singapore AI COE serves as a focused engineering and research hub dedicated to enterprise and sovereign AI applications. Our goal is to facilitate smooth AI workflow deployment into production by developing reusable software architectures targeting common industry challenges and contributing enhancements to open-source projects addressing enterprise deployment, runtime optimization, and platform management.

Located in Singapore, the team maintains a close connection with customers, partners, and core product groups, ensuring relevant development priorities, accelerated solution delivery, and collaborative innovation across the APAC region.

Role Overview

The AI/ML Engineer role involves a technical, hands-on approach bridging Enterprise AI development and direct customer architecture engagement. Within the Customer Engineering team, you design and deliver production-quality solution blueprints alongside strategic clients and technology partners, addressing operational hurdles in the region by producing replicable, extensible, and openly shared AI Quickstarts.

Career advancement here depends solely on technical expertise, architectural insight, and the capacity to autonomously implement end-to-end solutions in ambiguous settings, without responsibilities for team leadership, project management, or mentoring.

Key Responsibilities

• Create extensive, production-ready architecture blueprints addressing critical enterprise needs such as system resilience, scalable infrastructure, and network segmentation, allowing final production deployment to be completed by others.
• Develop open-source AI Quickstarts that encapsulate repeatable and modular technical architectures to resolve real-world industry problems and encourage ecosystem adoption.
• Work in partnership with external engineering teams, including semiconductor manufacturers, regional AI initiatives, and software vendors, to validate and ensure reliable integration of joint architecture blueprints across technology stacks.
• Design and embed automated testing frameworks, evaluation harnesses, and telemetry within blueprints to track metrics like latency, throughput, cost, and model accuracy.
• Integrate stringent data privacy, secure networking, and localized hosting considerations into designs to comply with regulations and manage risks in highly controlled environments.

Required Qualifications and Skills

• Possess a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or related quantitative disciplines.
• Strong foundation in software engineering best practices including clean code, test-driven development, CI/CD pipelines, and version control with Git.
• Excellent English communication skills to clearly explain complex architectures to engineers and stakeholders.
• Deep proficiency in Python for machine learning and systems programming; familiarity with Go or C/C++ is highly advantageous.
• Experience with deep learning frameworks like PyTorch and NLP/vision toolkits such as Hugging Face Transformers.
• Hands-on experience deploying containerized applications on Kubernetes or similar enterprise orchestration platforms.
• Understanding of MLOps workflows including model serving lifecycles, data ingestion, and automated packaging.

Desirable Expertise

• Platform and pipeline engineering experience with distributed computing tools such as Ray, ML workflow orchestration frameworks like MLflow or Kubeflow, and unstructured data parsing utilities like Docling.
• Knowledge in generative AI including LLM orchestration engines (e.g., LangChain, LlamaIndex), agentic workflows, tool-calling protocols, and model fine-tuning techniques.
• Familiarity with runtime optimization for model serving, utilizing technologies like vLLM and hardware acceleration across CUDA, ROCm, or emerging GPU/NPU architectures.
• Designing secure, isolated container networks and compliance-driven local inference environments for regulated deployments.
• Experience applying AI solutions in regulated fields such as financial services, public sector, healthcare, telecommunications, or manufacturing is a plus.

Why Join Us?

• Play a pivotal role in shaping open-source AI solution blueprints with tangible ecosystem impact.
• Focus purely on technical growth and engineering contribution without managerial duties.
• Engage with state-of-the-art technologies including advanced hardware and next-generation AI runtimes.

About Red Hat

Red Hat leads in enterprise open source software, offering Linux, cloud, container, and Kubernetes technologies globally. Our work environment promotes flexibility and inclusivity, welcoming innovation from all team members regardless of role or experience.

Inclusion and Equal Opportunity

Our culture embraces openness, collaboration, and diversity, striving for equal opportunity and acknowledgment of all voices. We invite applicants from all backgrounds to be part of our inclusive community.

Red Hat is an equal opportunity employer committed to affirmative action. We do not discriminate based on any protected characteristic by law. Accommodations are available for applicants with disabilities upon request.