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AI Engineer (London - Hybrid)

Simudyne

London, England, United KingdomJobPosted 6mo agoStill listed 2 days ago

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At a glance

Compensation
No compensation found
Location
London, England, United Kingdom
Work Authorization
Not specified

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Job overview

The AI Engineer will train and fine‑tune large‑scale foundation models for financial applications, scale training across multi‑GPU/TPU clusters, manage compute resources, build efficient inference pipelines, and implement distributed training strategies using JAX or PyTorch.

Skills & qualifications

RequiredNice to have

Skills

JAXPyTorchDeepSpeedFSDPAccelerateLoRAQLoRAPEFTWeights & BiasesMLflowDiffusion ModelsAutoregressive ArchitecturesTransformer ArchitecturesAttention MechanismsMixture‑of‑Experts ArchitecturesQuantizationModel CompressionStreaming LearningFinancial ModelingTime Series

Qualifications

Experience Training Models With 1B+ ParametersStrong Expertise in JAX and/or PyTorch at ScaleHands‑on Experience With Multi‑GPU/TPU Training and OptimizationDeep Understanding of Diffusion Models and Autoregressive ArchitecturesExperience With Distributed Training Frameworks (DeepSpeed, FSDP, Accelerate)Experience With Foundation Model Fine‑Tuning (LoRA, QLoRA, PEFT)Strong Understanding of Attention Mechanisms and Transformer Architectures

Full job description

Careers Open Positions AI Engineer (London – Hybrid) Location: London (Hybrid – 1-2 days/week in office) Reports to: Head of AI Key Responsibilities

  • Train and fine-tune large-scale foundation models for financial applications

  • Scale training across multi-GPU/TPU clusters with efficient parallelization

  • Manage compute resources and optimise training costs across cloud providers

  • Build efficient inference pipelines for production deployment

  • Implement distributed training strategies (data/model/pipeline parallelism)

  • Develop custom JAX/PyTorch implementations for novel architectures

  • Monitor and debug large-scale training runs with experiment tracking

Essential Requirements

  • Experience training models with 1B+ parameters

  • Strong expertise in JAX and/or PyTorch at scale

  • Hands-on experience with multi-GPU/TPU training and optimization

  • Deep understanding of diffusion models and autoregressive architectures

  • Experience with distributed training frameworks (DeepSpeed, FSDP, Accelerate)

  • Experience with foundation model fine-tuning (LoRA, QLoRA, PEFT)

  • Strong understanding of attention mechanisms and transformer architectures

Nice to Have

  • Experience with mixture-of-experts (MoE) architectures

  • Knowledge of quantization and model compression techniques

  • Experience with streaming/online learning at scale

  • Background in financial modeling or time series

  • Familiarity with MLOps tools (Weights & Biases, MLflow)

What We Offer

  • Work on cutting-edge AI for major financial institutions (LSEG, Barclays)

  • Access to significant compute resources (GPUs/TPUs)

  • Direct impact on core AI technology

  • Equity package

  • Competitive salary

  • Flexible hybrid working

Email us to apply. Looking forward to hearing from you!

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