Machine Learning Engineer

Description

ProntoPro is a marketplace for artisans and professionals.

We help millions of customers to find the professionals they need: a photographer for a wedding, a plumber, a guitar teacher, and many more. We are bringing meritocracy and transparency to a market which is currently opaque. We want to revolutionize both the way customers choose a professional and the way professionals find new customers.

We are a startup facing a hyper-growth: on March 2015 we used to be 2 people; today we are more than 100.Average age is 29 years old; we work in open spaces and minimize bureaucracy.Everyone at ProntoPro has great responsibilities and a direct impact on our success.

We have institutional investors such as Immobiliare.it and high profile angel investors coming from Google, Facebook, eBay, McKinsey and Unicredit.We are a startup, but without the typical risks of a startup.We already conquered the market in Italy, Austria, Switzerland, Germany, France, and Spain. And we want more!

We are looking for people willing to build a digital giant that has a strong impact on everybody's life. This is not a quiet job, we put our heart in it.

You will have visibility over the whole business and not just on your area of competence.

We strongly believe that everybody can give an important contribution, also from the architecture, product, and business strategy point of views.

You will be part of our Technology department, currently counting 20 people and expected to grow up to 30+ people during 2019.You will create a scalable product that will support ProntoPro hyper-growth.

You will work in an environment which is highly focused on tech trends and agile methodologies.In particular, you will play with the following stack: Python, Scala, Tensorflow, Keras, Pytorch, Kinesis, Spark, Hadoop, Airflow, Kubernetes, Drone.io, Travis, Docker, Git.We continuously strive for enriching/upgrading our tech stack and we cannot wait for your contribution!

You will also attend meetups/events and have the chance to speak about how we face and solve tech challenges at ProntoPro.

We are looking for a Machine Learning Engineer willing to join our Technology department.

• Develop intelligent systems based on traditional algorithms as well as the latest AI/DL technologies.
• Implement and optimize algorithms using open source libraries such as Scikit-Learn, Numpy, Scipy, Pandas, Tensorflow or Torch.
• Build tools for supporting experiments, development and debugging of deep and shallow machine learning models.
• Build sanity checks and dashboards for monitoring model performances.
• Build robust workflows for training, evaluation and inference at scale.
• Automate the deployment and operations leveraging the latest AWS cloud services.
• Work closely with our CTO, Data Engineers, Software Engineers, Product Owners and Data Scientists to design new features.

• Deep understanding of the bias-variance tradeoff.
• Solid knowledge of popular ML techniques and ability to apply them against real life problems.
• Solid engineering and coding skills; ability to write high performance production-quality code.
• Solid knowledge of REST APIs and microservice architectures.
• Good knowledge of Agile development and lean principles.
• Good knowledge of GIT versioning system.

• Experience with functional programming (Scala, Clojure).
• Experience with parallel computing using GPUs and CUDA.
• Experience with real-time evaluation of large data streams.
• Experience with Docker and Kubernetes.
• Contributor or author of relevant open source notebooks.
• Contributor or author of major open source GitHub repos.

• You will be invited to schedule a 15 minutes screening call with our global recruiters.
• Next, you will be invited to schedule a 30 minute phone call with a Tech Lead
• Next, you will be invited to schedule a 45 minutes technical and behavioral interview with a Tech Lead and possibly a peer.
• Next, you will be invited to schedule a 45 minutes behavioral interview with a founder or the CTO or a member of another department (this will change on a case-by-case basis).
• Successful candidates will then be made an offer.

Our tech teams are distributed among two HQs:

• Milan: via Fabio Filzi, 25 (map)
• Rome: via Marsala, 29/h (map)