Senior Machine Learning Engineer (Remote from EU)

About

PriceHubble is a B2B proptech company that develops valuation and analysis solutions for the residential real estate market. To get straight to the point, its solutions allow real estate professionals (investors, developers, banks, real estate agents, brokers, etc.) to evaluate their real estate assets as closely as possible, to advise their individual customers and to offer a digital and personalized experience. Big data and machine learning are at the heart of its model. PriceHubble is already present in 9 countries (Switzerland, France, Germany, Austria, Japan, the Netherlands, Belgium, Czech Republic and Slovakia) and now has more than 130 employees worldwide.

Job Description

PriceHubble is a PropTech company with over 185 employees, set to radically improve the understanding and transparency of real estate markets based on data-supported insights. We aggregate and analyse a wide variety of large scale datasets, and apply state-of-the-art machine learning to generate high-quality valuations and predictive analytics for the real estate market. We are headquartered in Zรผrich, with offices in Berlin, Hamburg, Paris, Vienna, Prague, Amsterdam and Tokyo. We work on international markets and we are backed by world-class investors. We have a startup environment, low bureaucracy, and an international team and business.

The opportunity

You will be part of the Data Products team, and collaborating with other experienced scientists and engineers to deliver world-class valuation and real-estate inference products. You will strive at Price Hubble and in the Data team if you value elegant and highly efficient engineering, and you derive your satisfaction from delivering very reliable products that delight customers.

Through your contributions, you will help to:

  • Deploy, monitor, optimise and scale AI-based prediction and insight services in production
  • Build infrastructure, automation and system to automate the management of models, data and insights delivery
  • Extract features from diversified data sources such as structured data, asset images, map data or satellite imagery at scale
  • Define, measure and automate dataset and model quality assurance
  • Analyse and annotate various datasets
We will also expect you to always stay at the forefront of ML engineering, quality management and data ops best practices in the industry.

Requirements

  • BSc or MSc in computer science or related fields
  • Excellent skills in object-oriented programming, data structures and algorithms
  • Proficient in the Python data science ecosystem
  • Experience with machine-learning in production: Tensorflow, scipy, machine-learning modelling
  • Practice using agile methodologies and devops practices
  • Hands-on experience working with any public cloud platform (AWS, Azure or GCP)
  • Experience with containerisation and container orchestration
  • Experience with Big Data systems like Apache Spark is a plus
  • You can design architectures to solve problems at scale
  • You value end to end ownership of projects, simplicity and getting the right things done
  • Eager to grow and learn, and to help create an harmonious engineering culture
  • Comfortable with collaboration in English and technical communication
  • Structured, didactic communicator and able to mentor other engineers and scientists

* We are interested in every qualified candidate who is eligible to work in the European Union but we are not able to sponsor visas.

Benefits

Join an ambitious and hungry team and enjoy the following benefits:

๐Ÿ’ฐ Competitive salary because we always want to attract the best talents.

๐Ÿ“˜ Learning & Development program - We want you to feel happy, confident about improving your skills, experience level as well as your personal development success.

๐Ÿข Very well-located offices with a great remote work policy and the possibility to work from different places.

๐Ÿ•“ Flexible working hours and work life balance.

Additional Information

  • Contract Type: Full-Time
  • Location: Paris, France (75002)
  • Possible full remote