Senior machine learning engineer (hybrid - lisbon)

As a Senior Machine Learning Engineer at Iterable, you will design and build the end-to-end machine learning systems that power intelligence across our product. You'll own the systems and models behind our ML products and help shape the direction of AI at Iterable.

O que vais fazer

• Build and ship core product ML capabilities, including send-time/frequency optimization, recommendation engines, and campaign personalization
• Own the full model lifecycle end-to-end: EDA, feature engineering, distributed training, production deployment, latency monitoring, and online experimentation (e.g., multi-armed bandits, ensemble models)
• Build and scale our data pipelines and serving architectures using Databricks, Spark, AWS, Ray, and Kubernetes
• Partner with Backend and Platform teams to elevate feature serving, improve overall data architecture, and establish engineering standards across the team
• Mentor engineers on the team and help set the technical direction for ML at Iterable
• Building, evaluating, and integrating new models that add intelligence into our core product
• Enhancing models that optimize send time and frequency of outgoing message campaigns
• Designing data pipelines that make it easy to implement and test new models
• Working with platform engineers to enhance our feature- and model-serving architecture
• Benchmarking and improving our multi-armed bandit implementation
• Building tools to visualize and debug features and models

O que é pedido

• 5+ years of hands-on MLE experience putting complex models into production at scale
• Databricks & Spark mastery: Real experience building, optimizing, and scaling production data pipelines using Databricks
• Production-level Model Engineering: Proven track record of taking deep learning and ensemble architectures from training through optimization to production deployment
• Production Code: Strong Python and/or Scala skills with an emphasis on readable, modular, and maintainable systems code
• Systems & Infra Experience: Hands-on work with microservice backends, distributed compute (Ray/Spark), and containers (Kubernetes)
• Pragmatism: You care more about serving latency, reliability, and measurable customer impact than novel theoretical architectures

Valorizado

• Prior work on large-scale recommendation systems
• Experience setting up feature stores or model observability tools
• Exposure to Infrastructure-as-Code (Terraform, Pulumi)

O que é oferecido

• Competitive salaries & meaningful equity
• Private Medical Insurance
• Life/Risk Assurance
• Meal Allowance: 8.55€ per day
• Community Days (days for us to give back to the community)
• Paid Annual Leave (22 days)
• Global Lifestyle Reimbursement Account
• Paid Sabbatical
• Complete laptop workstation
• The base salary range for this position in Lisbon, Portugal, is €66,500 – €88,000 per year (gross)

Investimento de tempo

Processo de entrevista

O nosso processo de recrutamento inicia-se com uma conversa com o Recruiter (cerca de 30 minutos), seguida de um Technical Screen de 50 minutos (problem-solving, code quality, code structure, data structure knowledge e performance). Na fase seguinte, temos duas sessões técnicas de 40 minutos cada: code review e system design. O processo termina com uma entrevista com o Hiring Manager para avaliar cultural fit.

Quanto paga este cargo

Este anúncio paga 213% acima da mediana

Benefícios e vantagens

• Acções da empresa
• Apoio ao home-office
• Ginásio & atividades desportivas
• Mais de 22 dias de férias
• Permite período sabático
• Perto de transportes públicos
• Seguro de saúde
• Suporte psicológico

Valores e cultura

• Ambiente de start-up
• Ambiente internacional
• Boa documentação
• Códigos de alta qualidade
• Equipa com senioridade elevada
• Escolha do trabalhador
• Igualdade de género
• Membros impressionantes na equipa
• Tecnologias de ponta