As a Machine Learning Engineer at Iterable, you will design and build the end-to-end machine learning systems that power intelligence across our product. As a high-tech marketing platform, we work with thousands of large-scale and diverse enterprise customers. The scale and diversity of these workloads — supporting personalization with deep customizability — present unique and exciting challenges for machine learning at production scale.
You will have real autonomy: from research and experimentation through to models running reliably in production, you'll own the systems and models behind our ML products and help shape the direction of AI at Iterable.
One of our core values is a growth mindset, and Iterable is a company where everyone can grow. If this role excites you, please apply — we value applicants for the skills they bring beyond a job description.
WHAT YOU'LL DO
Build and Ship ML Capabilities: Contribute to core product features, including send-time/frequency optimization, recommendation engines, and campaign personalization.
Execute Full Model Lifecycle: Perform EDA, feature engineering, distributed training, production deployment, latency monitoring, and online experimentation (e.g., A/B testing, multi-armed bandits, ensemble models).
Maintain & Scale Pipelines: Build and maintain scalable data pipelines and serving architectures using Databricks, Spark, AWS, Ray, and Kubernetes.
Collaborate Cross-Functionally: Partner with Backend and Platform teams to integrate feature serving, improve data architecture, and adhere to team engineering standards.
Continuous Learning: Participate in design reviews, expand your domain knowledge, and continuously improve code quality across our repositories.
WHAT WE'RE LOOKING FOR
Experience: 2–4 years of hands-on MLE experience deploying models into production environments.
Data Processing & Scaling: Practical experience building and optimizing production data pipelines using Databricks and Spark.
Production Model Engineering: Solid background in training, evaluating, optimizing, and serving machine learning and deep learning models in production.
Production Code: Proficiency in Python and/or Scala with a strong focus on clean, modular, tested, and maintainable code.
Systems & Infrastructure: Hands-on experience with containerization (Docker, Kubernetes), distributed compute frameworks (Ray or Spark), and microservices.
Pragmatic Mindset: Focus on customer impact, serving latency, and reliability alongside algorithmic performance.
BONUS POINTS
Experience with large-scale recommendation systems or personalization engines.
Familiarity with Feature Stores (e.g., Feast, Tecton) or ML observability platforms (e.g., Evidently, Arize).
Exposure to Infrastructure-as-Code (Terraform, Pulumi) and CI/CD pipelines.
YOU MIGHT WORK ON
Integrating and evaluating new models that add intelligence to our core product offerings.
Enhancing algorithmic models that optimize the send time and frequency of outgoing marketing campaigns.
Designing reliable data pipelines to accelerate feature extraction and model iteration.
Working with platform engineers to enhance feature- and model-serving latency.
Benchmarking and tuning multi-armed bandit algorithms.
Developing internal tools to inspect, visualize, and debug features and models.
WHAT WE OFFER
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 €55,000 – €68,000 per year (gross). This range is provided in anticipation of the requirements of the EU Pay Transparency Directive (2023/970), which EU member states are implementing into national law, and reflects the expected compensation at the start of employment for this role.The final offer will be determined based on your experience, qualifications, and performance throughout the selection process, while also ensuring alignment with our internal equity principles.
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Iterable is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Iterable does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender-identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Iterable also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Pursuant to the San Francisco Fair Chance Ordinance and other similar state laws and local ordinances, and its internal policy, Iterable will also consider for employment qualified applicants with arrest and conviction records.
