Role overview

ML Engineer

Requirements and responsibilities

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๐Ÿ’ผ About the job

  • Own ML models across their full lifecycle - from data pipelines and feature engineering to training, evaluation, deployment and monitoring; choosing the right metrics and guarding against leakage, overfitting and drift.
  • Run and improve our ML platform - own the team's GitOps CI/CD and release process, monitor serving endpoints, latency and load in Datadog, and define the SLOs and alerting that keep models reliable in production.
  • Turn ML into business value across the org - collaborate with risk, operational and product teams to spot and ship ML opportunities, from credit scoring to AI for operational intelligence, sharing your expertise through code reviews and tech watch.

To succeed in this job

  • You have 5+ years building and shipping ML in production: strong Python and SQL, solid ML fundamentals (evaluation, leakage, over/under-fitting), and clean, tested, reviewable code. We expect you to be familiar with some elements of our stack.
  • You're hybrid - hands-on with MLOps and infrastructure (data pipelines, monitoring, system design, live prediction / streaming) and at ease reasoning about latency, scale and reliability.
  • You're autonomous, analytical and business-driven, with professional English and working proficiency in French (the team's day-to-day language).

And it will be nice if you also

  • Have experience with GCP, Docker, or graph databases.
  • You have experience with LLMs, both as development tools and as components embedded in product systems.
  • Have a background in credit scoring, BNPL ("Buy Now Pay Later"), or financial services and fraud.

๐Ÿง˜ What's in it for you

  • Visible impact - your models directly move Alma's bottom line, and you'll see it in the scoring and debt collection KPIs.
  • A modern ML platform to build on and improve - a GitOps/MLOps stack (Argo CD, GitHub Actions, dbt, Datadog) you'll own and shape.
  • Real breadth - from core risk models to AI for operational intelligence, with genuine ownership across modelling and infrastructure in a small, autonomous team.

๐Ÿค‘ Compensation & benefits

  • Competitive salary based on 12 months
  • Profit-sharing and employee savings plan
  • Health insurance: 100% covered by Alma including family package
  • Disability insurance: 100% covered by Alma
  • Sport: partnerships with Gymlib and Classpass, or โ‚ฌ30/month reimbursement for your sports activities
  • Maternity/paternity leave: salary maintained at 100% during leave with no seniority requirement. Return to work at 4/5 schedule paid at 100% for 8 weeks.
  • Sustainable Mobility Package (FMD): โ‚ฌ544.80/year (excluding full-remote contracts)
  • Meal vouchers: โ‚ฌ10/day, 50% covered by Alma
  • Mental health: free access to MindDay platform
  • Paid time off: 25 days/year (+ additional paid leave granted for employees on executive contracts)
  • Access to our Learning & Development Platform
  • 2 weeks of full remote possible per year in summer

๐ŸŽฏ Interview Process

  • Video call with a Talent Acquisition team member to understand your path, motivation & present you the role.
  • Video call with your future manager to deep-dive a significant project you've owned, the team and the role.
  • Applied ML, coding and ML system design discussion with 2โ€“3 team members - a live, hands-on build to assess your craft, modelling judgment.
  • Fit interview with a senior leader to assess values, motivation and ways of working.
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Browse stack
FocusMachine Learning EngineeringRole area
Seniority signalSeniorCandidate level
StackCI/CD, Docker, GCPPrimary skills
Location40 accepted countriesEligibility

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