Backend Engineer – Machine Learning Services

Job description

What do we do?

We gather and process machine learning training data for AI applications internationally and have been providing services for cutting-edge AI businesses as well as Fortune 500 companies. We count Amazon, Sony and Portugal Ventures amongst our investors and are proud to be one of the fastest growing companies in the AI field.

How do we do it?

DefinedCrowd’s culture is about our four core values: Trust, Innovation, Passion, and Creativity. We like to think that we are a multi-talented, quirky and hard-working group dedicated to building a great platform, making our customers and community happy, and making our employees feel at home.

How can you help?

We are currently looking for talented new members across the world to join this energetic, hardworking and fun team in our Seattle headquarter, our R&D centers in Lisbon and Porto, or our office in Tokyo:


  • Select best options for software architecture based on engineering and business goals
  • Analyze trade-offs, recommend solutions and help move from ambiguity to clarity in early design phases
  • Work closely with internal stakeholders to bring Machine Learning capabilities into the core product

What do we offer:

  • The opportunity to learn the industry best practices
  • Flexible working conditions
  • International and diverse teams
  • Fresh fruit and a healthy working environment.

Location: Lisbon


Required Skills:

  • Background in the Computer Science field or related
  • At least 3 years of experience in a backend related role either in a web or infrastructure development context
  • Programming experience in one or more of the following languages: Python, Java, C++, C#, etc.
  • Knowledge in common networks protocols: HTTP, Web Sockets, RPC, etc.
  • Knowledge in message brokers like RabbitMQ, Azure Service Bus, etc.
  • Knowledge in data processing patterns and algorithms like: map reduce, hyperloglog, etc.
  • Basic understanding of data structures and their time/space complexity tradeoffs
  • Experience with Cloud technologies
  • Experience working with RDBMS as well as NoSQL systems like key-value stores, or document stores
  • Experience with Big Data technologies
  • Experience productizing Machine Learning