Senior ML Engineer

Primer
United Kingdom, Ireland
Workplace: RemoteFull timeFunction: Data Science & Machine LearningSkills: ["Mentorship","Experimentation","Problem-solving","Communication","Comfort with ambiguity"]

Own the full lifecycle of ML-powered features for initiatives in payments—from independent research and testing through training, deployment, and production monitoring. Productionize ML-driven routing decisions with strong MLOps practices (versioning, CI/CD, observability), partner with product/data/engineering to ship measurable outcomes, and bring a pragmatic approach to experimentation, evaluation, and mentoring as the ML team is formed from scratch.

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FursaFursa
Primer
Primer
3 hours ago

Senior ML Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 3 hours agoStatus: Live

Job Summary

Own the full lifecycle of ML-powered features for initiatives in payments—from independent research and testing through training, deployment, and production monitoring. Productionize ML-driven routing decisions with strong MLOps practices (versioning, CI/CD, observability), partner with product/data/engineering to ship measurable outcomes, and bring a pragmatic approach to experimentation, evaluation, and mentoring as the ML team is formed from scratch.
Location: United Kingdom, Ireland
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Own the full lifecycle of ML-powered features: research, testing, training, deployment, and production monitoring.
  • •Productionize ML-driven routing decisions across the payment flow, building supporting ML infrastructure (versioning, CI/CD, observability).
  • •Partner with product, data, and engineering to turn use cases into shipped outcomes with measurable impact.
  • •Lead experimentation and model evaluation with a pragmatic, impact-first mindset rather than chasing sophistication.
  • •Mentor other engineers in ML techniques and help establish reliable, repeatable ML patterns and practices as the function is built.

Pay and Benefits

Perks:EquityPrivate MedicalCo-workingHome OfficeLearning BudgetEquipment

Key Requirements

  • •Senior experience in ML engineering, data science, or applied research with real production deployments (API, batch, or streaming).
  • •Ability to think statistically: design and run experiments and A/B tests and interpret results.
  • •Strong Python skills with hands-on experience using ML libraries such as scikit-learn, XGBoost, TensorFlow, PyTorch, or Keras.
  • •Solid grounding in modern software engineering, infrastructure, and data tooling, plus understanding of MLOps challenges across the ML lifecycle.
  • •Familiarity with reinforcement learning (e.g., multi-armed/contextual bandits) and cloud experience (AWS preferred; GCP or Azure fine).
Experience:PaymentsE-commerceApplied research
Skills:MentorshipExperimentationProblem-solvingCommunicationComfort with ambiguity
Tech Stack:PythonScikit-learnXGBoostTensorFlowPyTorchKerasAWSGCPAzureCI/CDObservabilityA/B testingReinforcement learningMulti-armed banditsContextual bandits

Company Brief

Primer
Provides a unified, no-code / low-code payments infrastructure and orchestration platform that lets merchants connect, automate and optimise payment flows across processors, methods and partners to improve conversion and reduce friction.
Industry: Fintech Infrastructure
Company Size: Medium (51 to 250 employees)
Growth: Scaleup
Valuation: USD 250M to 500M
Funding: Series B
Headquarters: London, United Kingdom
Founded: 2020
WebsiteLinkedInGlassdoor