Senior Machine Learning Operations Engineer (Remote from EU)
Paris, Île-de-France, France
Applications have closed
PriceHubble
Leading the development of Data & explainable AI-driven real estate valuations and insights globally.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 Zürich, 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 high scale, customer-facing real-estate inference products. You will strive at PriceHubble 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
- Define, measure and automate dataset and model quality assurance
- Optimise and streamline data exploration, model training, deployment and serving processes to achieve insights quality and service quality SLOs
We will also expect you to always stay at the forefront of ML engineering, quality management, cloud 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
- Practice using agile methodologies and devops methods
- Hands-on experience working with public cloud platforms (AWS, Azure or GCP)
- Experience with machine-learning in production: Tensorflow, scipy, Keras…
- Experience with ML ops at scale in the cloud: K8s, Kubeflow, Dataproc, Sagemaker…
- Experience with containerization and container orchestration
- Experience with Big Data systems like Apache Spark and Hadoop 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:
💰 Competitive salary because we always want to attract the best talents.
📘 Learning & Development program - We want you to feel happy, confident about improving your skills, experience level as well as your personal development success.
🏢 Very well-located offices with a great remote work policy and the possibility to work from different places.
🕓 Flexible working hours and work life balance.
Tags: Agile AWS Azure Big Data Computer Science Dataproc DevOps Engineering GCP Hadoop Keras Machine Learning Model training OOP Python SageMaker SciPy Spark TensorFlow
Perks/benefits: Career development Competitive pay Flex hours Startup environment Team events Transparency
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