Senior AI Infrastructure Engineer: Training & Inference

Fin; Greater London; Hybrid; GBP 120.000 - 180.000; Vollzeit

Zusammenfassung

Fin, part of Salesforce, is hiring Senior+ AI Infrastructure Engineers to build scalable training and inference systems for its next‑generation AI products. You will own end‑to‑end pipelines from data prep to distributed training and production inference, with a strong emphasis on low‑latency services and GPU performance.

Collaboration with ML scientists and mentoring peers are also key parts of the role. You will work in a hybrid setup in London, contributing to a world‑class AI infrastructure

Qualifikationen

• 5+ years of software engineering experience and a track record of shipping high‑quality products or platforms.
• Degree in Computer Science, Computer Engineering, or related field (or equivalent experience).
• Hands‑on experience with model training or model inference at scale, or low‑level GPU work (CUDA/Triton).

Aufgaben

• Implement and scale training pipelines for large transformer and LLM models from data ingestion to distributed training and evaluation.
• Build and optimize inference services with low latency and high reliability, including autoscaling and routing.
• Tune GPU kernels and improve utilization across training and inference stacks.
• Collaborate with ML scientists to implement cutting‑edge training/inference methods and bring them to production.
• Mentor and develop other engineers and raise technical standards across Fin's AI platform.

Kenntnisse

Model training

Model inference

GPU programming

CUDA

Triton

Python

Go

Clear communicator

Ausbildung

Degree in Computer Science

Tools

Kubernetes

AWS

Jobbeschreibung

Fin, part of Salesforce, is hiring Senior+ AI Infrastructure Engineers to build scalable training and inference systems for its next‑generation AI products. You will own end‑to‑end pipelines from data prep to distributed training and production inference, with a strong emphasis on low‑latency services and GPU performance.

Collaboration with ML scientists and mentoring peers are also key parts of the role. You will work in a hybrid setup in London, contributing to a world‑class AI infrastructure