AI & Distributed ML Systems Engineer

DUDE CHEM

London

On-site

NOK 1,328,314 - 1,992,472

Full time

14 days+

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Benefits offered by this job

Relocation support
Learning allowance
Health & wellness
Social events
Parental leave

Job summary

Helsing is seeking an experienced ML/AI engineer to extend our PyTorch-based DL frameworks and scale our distributed training infrastructure. You will design data strategies for very large datasets and work at the intersection of ML and systems engineering.

Join a mission-driven team focused on responsible AI in defence. You will contribute to robust, scalable platforms and collaborate across cross-functional teams to maximize training throughput and developer velocity.

Qualifications

  • MSc/PhD in CS or STEM with ML/DL focus.
  • Strong Python programming and fluency in major DL frameworks; able to implement custom layers and distributed training loops.
  • Clear communicator with ability to contribute to internal engineering culture.
  • First-principles mindset; quickly translate research into code.
  • Experience debugging production ML pipelines and addressing numerical/performance issues.

Responsibilities

  • Extend our DL frameworks (PyTorch-based) for diverse use cases.
  • Scale infrastructure and tooling for faster, larger distributed training.
  • Design data strategy to support large-scale datasets and efficient storage.

Skills

Python
PyTorch
JAX
TensorFlow
Distributed training
Performance tuning
Machine Learning

Education

MSc/PhD in Computer Science or STEM

Tools

Slurm
Kubernetes
Ray
NCCL

Job description

Helsing is seeking an experienced ML/AI engineer to extend our PyTorch-based DL frameworks and scale our distributed training infrastructure. You will design data strategies for very large datasets and work at the intersection of ML and systems engineering.

Join a mission-driven team focused on responsible AI in defence. You will contribute to robust, scalable platforms and collaborate across cross-functional teams to maximize training throughput and developer velocity.

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