Senior MLOps Engineer

Futuris Recruitment Ltd; Stockholms kommun; On-site; SEK 1,000,000 - 1,600,000; Full time

Benefits offered by this job

Stock option plan

Job summary

Futuris Recruitment Ltd in Stockholm is seeking a senior ML infrastructure engineer to own the training infrastructure spanning on-prem GPUs and cloud capacity on AWS. You will scale the existing setup so ML engineers can focus on models rather than machines.

You will ensure end-to-end reproducibility, manage GPU environments, and keep costs sensible while protecting customer data. The role requires 5+ years of ML infra experience and fluent English, onsite in Stockholm.

Qualifications

• 5+ years building and operating ML infrastructure.
• Experience with GPUs, driver/CUDA issues and cloud capacity management.
• IaC with Terraform and Terragrunt; strong AWS skills.
• Data locking and experiment reproducibility are critical.
• Fluent English; on-site Stockholm.

Responsibilities

• Scale training infrastructure across on-prem GPUs and AWS cloud.
• Ensure end-to-end reproducibility of datasets, experiments and models.
• Support GPU environments that pause, resume and stay ready across machines.
• Control GPU spend and ensure data security.
• Collaborate directly with ML engineers to remove blockers.

Skills

ML infra

GPU handling

AWS

Terraform

Terragrunt

Data security

Reproducibility

English fluency

Tools

Terragrunt

CUDA drivers

Job description

The Position

You'll be working with a rapidly growing deep-tech startup building a platform for the manufacturing industry and apply ML/AI to how physical products are designed and produced. The ML team is shipping, and the GPU platform underneath it now needs a dedicated owner. You’ll take the training and evaluation infrastructure that already works and decide how it scales, so the ML engineers can focus on models rather than machines. This is a high-ownership role with very little process between you and the decisions.

What you’ll work on

• Training infrastructure across on-prem GPUs in the office and cloud capacity on AWS
• End-to-end reproducibility: versioned datasets, tracked experiments, and every model traceable back to the data it learned from
• The infrastructure behind their generative design agents and the evaluations that test them
• Interactive GPU environments that pause when idle, keep their state, and resume within seconds on any machine
• Keeping GPU spend under control and customer data secure
• Working directly alongside the ML engineers and clearing whatever slows them down

Requirements

• 5+ years experience building and running ML infrastructure
• Comfortable working directly with GPUs, from driver and CUDA issues through to finding capacity and keeping cloud bills sensible
• IaC with Terraform/Terragrunt and strong cloud skills (Ideally AWS)
• You get uneasy when an experiment can’t be rerun or data isn’t properly locked down, and you build systems that prevent both
• Fluent English speaker, able to work onsite in Stockholm.

Nice to have: some time on the modelling side yourself, or experience running LLM-based agents for real users

The offer

• Above market Base salary
• Attractive Stock option plan
• A small, skilled but humble team that writes things down, proposes before it builds, and measures before it claims