AI Engineer - Inference (AI)

Location: Singapore or Australia (Launceston, Hobart, Sydney, Melbourne)

Company

hirify.global Technologies develops and operates energy-efficient AI infrastructure and the hirify.global AI Cloud GPU platform across Asia Pacific.

What you will do

• Build, operate, and improve self-hosted AI inference services for internal applications, customer-facing products, and future Inference-as-a-service offerings.
• Design model-onboarding workflows covering compatibility validation, packaging, runtime selection, optimization, deployment, endpoint registration, testing, release, and lifecycle management.
• Provision secure, scalable endpoints for generation, RAG, embeddings, reranking, batch, multimodal, tool-calling, and agentic workloads.
• Develop deployment templates, APIs, SDKs, configuration standards, and self-service workflows for model endpoint management.
• Optimize inference performance through quantization, compilation, batching, caching, routing, memory optimization, distributed parallelism, and GPU profiling.
• Build benchmarking, observability, regression-testing, capacity-management, and security capabilities while collaborating with Platform, DevOps, Infrastructure, Security, Product, and AI applications teams.

Requirements

• 5+ years of software engineering experience, including 3+ years in AI inference, model serving, ML systems, high-performance computing, distributed systems, or comparable performance-critical environments.
• Production experience with model-serving platforms, inference APIs, GPU-backed services, AI developer platforms, or multi-tenant AI systems.
• Hands-on experience with inference frameworks such as TensorRT-LLM, TensorRT, SGLang, vLLM, Triton Inference Server, NVIDIA Dynamo, NVIDIA NIM, or equivalent technologies.
• Strong knowledge of the NVIDIA AI stack, including CUDA, cuDNN, NCCL, TensorRT, GPU profiling, distributed communication, and GPU performance analysis.
• Strong Python skills and working proficiency in C++ or Go, plus experience with Kubernetes, containers, CI/CD, GitOps, APIs, autoscaling, observability, and production platform operations.
• Experience with distributed inference, GPU topology, benchmarking, performance profiling, security, governance, tenant isolation, quotas, rate limiting, and data protection.

Culture & Benefits

• Permanent full-time employment.
• Founder-led environment with accessible leaders, fast decision-making, and limited bureaucracy.
• Early ownership and opportunities to grow into new technical domains.
• Work alongside experts in AI infrastructure, energy systems, and next-generation compute.
• Contribute to sustainable AI factories designed to strengthen the energy grid and surrounding communities.