Machine Learning Engineer (Paris or Berlin)

Description

PriceHubble is a PropTech company, set to radically improve the understanding and transparency of real estate markets based on data-driven insights. We aggregate and analyse a wide variety of data, run big data analytics and use state-of-the-art machine learning to generate stable and reliable valuations and predictive analytics for the real estate market. We are headquartered in Zürich, with offices in Paris, Berlin and Tokyo. We work on international markets. We are backed by world-class investors. We have a startup environment, low bureaucracy and international team and business.As a machine learning engineer, you will work closely with data scientists to engineer ML valuation frameworks at scale. You will implement ML algorithms paying much attention to scalability and ease of use. You will own productionalization of models developed by the team. Furthermore, in order to help data scientists be more effective in their work, you will develop various tools ranging from monitoring of model performance to visualization of data.

Responsibilities

  • Implement and optimize scalable machine learning algorithms.
  • Extend existing internal ML libraries and frameworks.
  • Productionalize and serve models.
  • Develop tools to monitor models’ performance.
  • Develop tools to visualize data.
  • Enable industry standard CI/CD and reliable model versioning.

Your profile

  • Software engineer with experience in algorithms, data structures, and OOP.
  • Good understanding of ML fundamentals and existing ML libraries.
  • Experience in implementing end-to-end libraries following high-quality code standards.

Requirements

  • Msc in Engineering or Computer Science with at least 3 years of experience in algorithms / OOP, and a good understanding of data science fundamentals.
  • Strong programming experience in Python + at least one compiled language (C/C++, Java).
  • Ability to write high-quality production code. Familiarity with code best practices and design patterns.
  • In-depth understanding of data structures and algorithms.
  • Strong analytical and mathematical skills.
  • Knowledge of our tech stack (or similar technologies) is an advantage: pandas, luigi, (Py)Spark, tensorflow, postgreSQL, docker, kubernetes, GCP.
  • Comfortable working in English; you have a great read, good spoken command of it.

Benefits

🕓Flexible work hours

👖Casual dress code

🍏Free snacks, fruits, coffee, beers, sodas

🍺Thursday drinks

✈️ Relocation package

📘L&D program

🏢Well-located offices

💰Competitive salary