Senior Machine Learning Engineer (Recommendation Systems & Personalization)
Ish ta'rifi
Local opportunities, international opportunities Work with colleagues and customers across Europe to build solutions that make a meaningful impact.
Responsibilities:
- Develop real-time product and bundle recommendation engines, including dynamic slot placement optimized for conversion and margin.
- Build targeted promotion algorithms: personalized coupon and points issuance, behavioral triggers and dynamic bundling.
- Scale the multi-market customer segmentation engine (behavioral, demographic, psychographic and lookalike audiences, wallet push).
- Extend personalization models across web, app and in-store employee touchpoints.
- Build and operate ML pipelines, from feature preparation in BigQuery and Snowflake to deployment and monitoring.
- Design and evaluate A/B tests to prove the business impact of each model.
- Hands-on experience building ranking or recommender systems that run in production.
- Strong Python and SQL skills;
experience with TensorFlow or PyTorch.
- Solid grounding in model evaluation and validation, both offline metrics and online results.
- Experience designing and analyzing A/B tests and experiments.
- MLOps experience: ML pipelines, model deployment, performance monitoring and CI/CD.
- Experience with cloud data warehouses, ideally BigQuery and/or Snowflake, and pipeline orchestration with Airflow.
- Experience with real-time or low-latency model serving.
- Experience with promotion, pricing or uplift modeling (e.g. coupon targeting, bundling).
- Customer segmentation and lookalike modeling across several markets.
- Infrastructure as code with Terraform.
- Experience on GCP ML tooling such as Vertex AI.
- Background in retail or e-commerce personalization.
- Fluent English for working in an international team.
To live a wholesome experience inside and outside our offices, we need to take care of our overall wellbeing, from the physical aspect to creating a healthy work-life fusion and looking at learning as a lifelong journey and a shared responsibility between our people and our organisation.
- Physical Wellbeing
Our wellbeing program includes medical insurance, In-house fitness trainer available remotely and 1 on 1 remote sessions with our Sports and Health Coach focused on nutrition counselling and tailored training plans.
- Work-Life Fusion
Start with at least 21 vacation days (based on seniority) and earn 1 extra day for each completed year of collaboration — up to 29 days — depending on your tenure in the company and/or industry. Enjoy the flexibility to work from both home and the office.
- Growth opportunities
We focus on long-term learning programmes that develop both technical and non-technical skills incrementally. Together with your Career Coach you will discuss what are learning resources and platforms you can access in order to develop your skills.
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Ключевые навыки
- Python
- SQL
- ML
- Recommendation Systems
- Ranking Algorithm
- Personalization
- PyTorch
- MLOps
- A/B Testing
- Model Evaluation
- ML Pipelines
- BigQuery
- Snowflake
- Apache Airflow
- GCP
- ETL
- Vertex AI
- Terraform
- Английский — C1 — Продвинутый
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