Specialised AI Engineer

Responsibilities

Our talent team is representing a confidential AI cloud infrastructure company seeking a Specialised AI Engineer to join their core platform team. This is a hands-on, high-impact role building distributed systems that power large-scale AI workloads.

You'll design, build, and optimise scalable AI platform systems in one or more of the following areas:

• Inference optimisation: KV cache management, continuous batching, speculative decoding, quantisation (INT8/4, FP8), sparsity, pruning, and model compression
• Post-training services: Fine-tuning (LoRA, QLoRA, adapters, full fine-tuning), alignment (RLHF, DPO, reward modelling), agentic RL (tool calling, off-policy training, parallel thinking, decoupled sampling and updating), dataset curation and data processing workflows
• Evaluation and benchmarking systems: Model quality, safety, and regression; system performance (latency, throughput, cost); real-world behaviour and feedback loops

Additional responsibilities include:

• Developing and optimising distributed systems for GPU/accelerator workloads, focusing on scalability, reliability, and efficiency
• Conducting performance analysis and bottleneck investigations across training, post-training, and inference components
• Collaborating with research, infrastructure, and product teams to build platform components based on customer demand and industry direction
• Building developer-facing APIs, SDKs, and tooling that enable other engineers to effectively use AI services

What We're Looking For

Must-have experience:

• 5+ years building production systems in machine learning, distributed systems, or high-performance infrastructure
• 4+ years of hands-on experience in at least one core area within large-scale, production AI environments (AI labs, hyperscalers): inference optimisation, large-scale training/pre-training systems, post-training (fine-tuning, alignment, distillation), or evaluation and benchmarking frameworks
• Strong hands-on expertise in at least one of the above areas, with working knowledge across others
• Proven ability to design, optimise, and operate systems at scale with strong understanding of performance trade-offs across latency, throughput, cost, and model quality
• Deep understanding of transformer architectures, LLMs, and/or multimodal models, including their behaviour in production systems
• Strong proficiency in Python and PyTorch, with a track record of building production-grade ML systems
• Experience with distributed compute and training paradigms (data/model parallelism, sharding, scheduling)
• Experience working close to the hardware/software boundary: GPU/accelerator optimisation (CUDA, ROCm, or similar), memory management and system-level performance tuning
• Experience building or operating production inference or training systems at scale
• Ability to design clean abstractions, APIs, and reusable systems for other engineers
• Strong engineering fundamentals with a track record of writing maintainable, well-tested, production-quality code

Preferred experience:

• Large-scale and high-load production systems development
• Containerised, distributed environments (Kubernetes, large-scale clusters)
• Contributing to or working with widely used/open-source AI frameworks or systems
• Advanced inference optimisation techniques (KVCache, MoE, adaptive batching, gradient checkpointing)
• API development using OpenAPI 3.0+ specifications
• Efficient training and inference evaluation strategies with demonstrated success in improving model efficiency

How We Work With You

When you apply through Get A Job.ai, our recruiting team will:

• Review your application and conduct an initial screening to understand your background and specialisation areas
• Discuss the role in detail, including the specific technical challenges and team structure
• Submit qualified candidates directly to our client for consideration
• Guide you through the interview process and provide feedback at each stage

Important: Please apply only through Get A Job.ai. Do not contact the client directly, as we are managing this search exclusively.

Pay

Compensation details will be discussed during the screening process based on your experience level and specialisation.

Location: Remote

Get A Job.ai is an equal opportunity recruiter. We encourage applications from candidates of all backgrounds, experiences, and abilities, and we work with clients who share our commitment to building diverse and inclusive teams.