Machine Learning Engineer

Description

Full-time, permanent (tempo indeterminato).

Milan, Corso Como 15. It’s fine if you prefer to work remotely sometimes. We offer substantial support for relocation, including finding an apartment in Milan and paying the rent for twelve weeks.

Generous, top of market, and moreover can grow very rapidly and include stock options, depending on your performance. Breakfast, lunch, and snacks are paid-for, when you work from the office. You’ll receive the latest Mac, iPhone, and wireless noise-cancelling Bose headset.

You’ll help us to shape the next generation of our products. You’ll work closely with Data Scientists and Software Engineers, architecting scalable solutions to deploy ML models in the cloud. You’ll focus on data wrangling, clean-up, and transformation, while Data Scientists focus on modeling and research. Our diversified portfolio of mobile apps is an extraordinary playground to experiment with ML systems and data architectures. You’ll get the chance to work across structured and unstructured data, and you may end up dealing with predictive models, text mining, time-series, and recommender systems. You’ll play a key role in choosing the best tools and infrastructure for the job, continuously testing competing approaches and technologies.

A few examples of your responsibilities:

• Work hand in hand with Data Scientists and Software Engineers to design, architect and deploy scalable ML systems in the cloud.
• Operate and maintain ML models in production, continuously iterating to make them more robust.
• Develop data loading/ETL processes to create analytical variables and metrics for Data Science.
• Refactor the code emerging from research efforts into reusable libraries, APIs, and tools.
• Write clear, efficient, tested, and high-quality code. Communicate and document solutions and design decisions to technical and non-technical project stakeholders.
• Contribute to the evolution of development standards and design patterns, playing an active role in pursuing engineering excellence through mentoring, workshops, and code reviews.
• Become an expert in cloud-based data solutions. Depending on the ML use case, you may need to investigate how to deploy Docker containers on Kubernetes, how to architect data pipelines on Spark, or how to parallelize hyperparameter searches on Dask, just to name a few.

What We Offer

• Huge impact. You’ll contribute to the foundation and scale-up of a center of excellence for Big Data and AI, in a hands-on engineering role. You’ll tackle real-world problems on real-world data, shaping solutions for tens of millions of users.
• Ownership. You’ll take responsibility for your products, playing a key role in decision making and problem-solving.
• Meritocracy and career opportunities. You’ll join a fast-growing tech company in a period of exploration into new product lines and technological frontiers. You’ll work on high-potential projects in a meritocratic environment, and you’ll have access to worldwide-competitive career opportunities.
• Talented, knowledgeable colleagues. You’ll get the chance to learn (and teach to!) some of the brightest and most skilled people you’ll ever meet. Your talent is going to blossom here.
• Cool tech stack. We strive to use the best, most modern tools and technologies, and when they fall short of our expectations we invent our own. It’s a geek’s paradise.
• Own products. We don’t work for clients, but only develop our own apps. Freed from politics, we can move fast and be daring.
• Fun, young environment. We have near-zero hierarchy and a very relaxed workplace. Also, we’re 28 years old on average and often hang out together, so you might actually end up making new friends!
• Top-notch office. Our office is amazing! We designed it ourselves and it goes beyond excellent functionality by offering all sorts of amenities, such as foosball tables and gaming consoles.
• International reach. Our audience is wildly international. Our company language is English. We’re a global reality.

What We Look For

• Passion for the topic. You have a long-standing, proven passion for scalable architectures in the cloud. You take pride in finding the right tool for the job, and you love to engineer beautiful code.
• Strong background in computer engineering. Mastering of a few high-level languages (Python, Java or other OOP languages), as well as familiarity with Linux/Unix/Shell environments. Working knowledge of major algorithms and data structures, computer architecture, operating systems and DBMS. Knowledge or experience in machine learning modeling (classification, regression, ranking, clustering, and recommending) is a plus, but we welcome any developer willing to learn.
• Reasoning and depth of learning. You’re structured and creative enough to solve most challenging problems independently, given the necessary knowledge. You learn new concepts and skills rapidly, and look to understand stuff truly in depth.
• Drive. You’re energetic, hard-working, and persevere through adversity until the job is done, and done well. You get turned on by getting results, and always aim for excellence in what you do.
• Pragmatism. Far from being too academic or obsessive in your perfectionism, you understand that, when getting things done in a competitive world, speed is often as important as quality.
• Curiosity and initiative. You love exploring and you’re entrepreneurial in seeking out new opportunities and testing new ideas of your own accord. You don’t just wait to be told what to do all the time.
• Attention to detail. You care to get the small things right as well as the big ones. You’re meticulous in checking that your code will work exactly as expected.
• Diligence, organization. You can blindly be entrusted with big responsibilities as well as small, more menial tasks.
• Humbleness. You’re down to earth, eager to listen to people’s feedback and constructive criticism, and ready to get your hands dirty with whatever the team needs to succeed.
• Proficient in English. You read and write proficiently, and speak at a conversational level in English.