Constructor

Data Engineer: Ranking Team (Remote)

Remote Barcelona, Spain
USD 90k - 110k
Spark AWS Streaming Kafka API Machine Learning Python
Description

Constructor is a new kind of search engine and product discovery platform built primarily on AI. It focuses primarily on ecommerce and powers some of the biggest ecommerce sites in the world such as Sephora, Petco, Under Armour, Birkenstock, Home24 and many more. . Constructor's AI-first solutions make it easier for shoppers to discover products they want to buy and for ecommerce teams to deliver highly personalized experiences that drive impressive results. Optimizing specifically for ecommerce metrics like revenue, conversion rate and profit, Constructor generates consistent $10M+ lifts for some of the biggest brands in ecommerce. Constructor is a U.S. based company that was founded in 2015 by Eli Finkelshteyn and Dan McCormick.

The Ranking team, within the Machine Learning department, plays a central role in implementing algorithms that optimize our customers’ business KPIs like revenue and  conversions. We focus on metrics over features, supplying our ranking algorithms with powerful capabilities that bring value to customers. 

The team is cross-functional, consisting of ML, BE, and FE engineers as well as  designers. As a member of the Ranking team, you will be surrounded by and encouraged to use world-class analytical, engineering, and machine learning techniques on big data to evolve and scale our search algorithms. The Ranking team owns all stages of product ranking for Constructor’s Search, Browse and Autocomplete experiences, including base ranking, ML ranking, personalization, and ranking explanation.

A primary focus of the Ranking team is to develop a platform that allows internal and external users to configure ranking for business needs and experiment with new signals easily. Related to that focus, the Ranking team owns: 

  1. An online high load distributed REST based ranking service deployed in the cloud and developed in Python programming language 
  2. Offline Data Pipelines that are used for data processing (Python, Spark/Databricks), ML model training and  model signals delivering (e.g. Feature Store), Ranking configuration for a given Customer.

Challenges you will tackle

We're looking for a senior engineer with at least 4 years of experience who has solid skills in any programming language (ideally Python), big data engineering, web services, cloud providers (ideally AWS), and is willing to build many diverse things to develop the Platform.

A primary focus of this job is to design, improve and maintain the Ranking Platform in close collaboration with other engineers from the Ranking team. The job can consist of, but is not limited to:

  • Improve Ranking Platform usability for fellow engineers
  • Build / deploy / support robust highload real-time (ML) system(s) for personalized search and browse experiences. 
  • Collaborate with technical and non-technical business partners to develop / update ranking functionalities (within & outside the team)
  • Optimize current ranking service performance
  • Optimize signals delivery and retrieval (e.g. Feature Store) for ML models inference

Hard skills

  • At least 4 years of experience in software development, with proficiency in Python programming language.
  • Experience with big data tools: experience with Apache Spark or any other map-reduce framework is a must.
  • Experience with data pipeline orchestration: strong understanding of ETL/ELT processes using orchestration tools like Airflow, Luigi, or cloud-native services (AWS Glue, Step Functions).
  • Experience working with large datasets, distributed systems, NoSQL and relational databases, and caching solutions, ensuring scalability and low-latency performance.
  • Experience with performance optimization: proven experience optimizing web services & data pipelines to improve speed, reliability, and scalability.
  • Experience with real-time data processing: Experience building and supporting high-load real-time data platforms for ranking and personalization systems. Familiarity with streaming architectures using Apache Kafka, Kinesis, or Pulsar is a plus.
  • Experience with data ingestion pipelines: Ability to design and maintain robust data ingestion systems that pull data from multiple sources (e.g., APIs, databases, event streams) into the platform in real-time.
  • Experience with monitoring and alerting: Experience with setting up monitoring and alerting (e.g., Prometheus, Grafana, Datadog) to ensure the reliability and health of data pipelines and platforms in production.

Soft skills

  • Experience collaborating in cross-functional teams.
  • Excellent English communication skills.
  • Enjoy helping others around you grow as developers and be successful
  • Pick up new ideas and technologies quickly, love learning and talking to others about them
  • Love to experiment and use data and customer feedback to drive decision making
Constructor
Constructor
Artificial Intelligence (AI) Machine Learning SaaS Search Engine Semantic Search

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