Lead AI Inference & Performance Engineer

Dizzaract; Abu Dhabi; On-site; AED 420,000 - 720,000; Full time

Benefits offered by this job

Health insurance

24 days annual leave

Modern office in Yas Creative Hub

Job summary

Dizzaract is seeking a Lead AI Engineer for Inference Serving & Performance to own the technical direction of our inference stack. You will work across inference serving, GPU performance, distributed systems, benchmarking, and model optimisation to accelerate serving infrastructure while preserving quality.

This senior role requires hands‑on leadership, setting engineering standards, and guiding teams across serving, metrics, and testing.

Qualifications

• Strong hands‑on experience building, optimising, or operating LLM inference‑serving systems in production.
• Deep understanding of inference stacks such as vLLM, SGLang, TensorRT‑LLM, or similar.
• Understanding of paged attention, continuous batching, disaggregated serving, KV-cache management, and modern inference architectures.
• Experience with CUDA or Triton for GPU performance engineering.
• Experience with MoE models, expert parallelism, and distributed execution.
• Experience with model quantisation and measuring quality against full‑precision references.
• Strong benchmarking experience including load generation and latency percentiles.
• Distributed systems knowledge for routing, scheduling, and workload distribution.
• Proven technical leadership in inference serving or ML infrastructure.

Responsibilities

• Inference Serving: Own and improve the FAR Labs inference serving stack and related optimisations.
• Serving Performance: Improve throughput, latency, memory efficiency, and cost while maintaining model quality.
• GPU Performance Engineering: Identify bottlenecks across the stack using CUDA, Triton, profiling, and memory optimisations.
• Mixture-of-Experts Serving: Drive efficient serving of MoE models with expert parallelism and load balancing.
• Quantization & Model Optimisation: Implement quantization and measure against full‑precision references.
• Benchmarking & Measurement: Own reproducible benchmarking across performance, quality, and cost.
• Distributed Serving: Make routing, scheduling, and caching decisions across diverse hardware environments.
• Technical Roadmap: Define serving and measurement roadmap and prioritise improvements.
• Engineering Standards: Establish standards around inference performance, reproducibility, and production readiness.
• Technical Leadership: Mentor engineers and influence architecture while remaining hands‑on.

Skills

Inference serving

Performance optimization

GPU utilisation

Distributed systems

Benchmarking & measurement

Technical leadership

Speculative decoding

English (Advanced)

Tools

vLLM

SGLang

TensorRT-LLM

CUDA

Triton

Job description

Dizzaract is seeking a Lead AI Engineer for Inference Serving & Performance to own the technical direction of our inference stack. You will work across inference serving, GPU performance, distributed systems, benchmarking, and model optimisation to accelerate serving infrastructure while preserving quality.

This senior role requires hands‑on leadership, setting engineering standards, and guiding teams across serving, metrics, and testing.