BJSS is hiring a

Machine Learning Engineer

Porto, Portugal

About Us 

We’re an award-winning innovative tech consultancy - a team of creative problem solvers. Since 1993 we’ve been finding better, more sustainable ways to solve complex technology problems for some of the world’s leading organisations and delivered solutions that millions of people use every day. 

In the last 30 years we won several awards, including our most recent inclusion in the Forbes World's Best Management Consulting Firms report.  

Operating from 26 locations across the world, we bring together teams of creative experts with diverse backgrounds and experiences, who enjoy working and learning in our collaborative and open culture and are committed to world-class delivery.  

Our story in Portugal started in 2020 with a small office in Lisbon. The team is now over 100 across Lisbon and Porto, and we are the perfect blend of national and international collaboration and reputation.  

We want to continue to grow and need people just like you! 

About the Role

As a Machine Learning Engineer at BJSS, you’ll collaborate with some of the brightest and best in the industry as part of multi-disciplinary teams. You’ll work in a fast moving, agile environment and will be involved in implementing machine learning algorithms, building production Machine Learning systems and developing MLOps processes.

You’ll help deliver some of the most exciting digital programmes around for clients in a range of industries by:

  • Applying cross-disciplinary thinking
  • Building a deep understanding of business domain and user needs and making sure that the actual business value is unlocked as early as possible
  • Thinking holistically and treating data as a business service

About You

You should apply if you have:

  • Proven Machine Learning Expertise: Hands-on experience in developing and deploying Machine Learning models in production environments. Solid grasp of common Machine Learning algorithms and their application
  • Software Engineering Skills: Proficiency in Python, with a focus on writing testable, modular code. Strong understanding of data structures, data modeling, and software architecture
  • Data Science Library Knowledge: Deep understanding of key Data Science and Machine Learning libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow), with a preference for PySpark experience
  • Model Productionisation: Experience in taking Machine Learning models from development to production
  • CI/CD and MLOps Experience: Familiarity with Continuous Integration and Continuous Deployment pipelines, especially in a Machine Learning or DevOps context
  • Cloud Platforms: Experience building solutions using major cloud services (Azure, AWS, GCP)
  • Analytical thinking: Exceptional problem-solving abilities backed by analytical rigor

Some of the Perks 

  • Coverflex Flexible Benefit allowance – you can choose to spend your allowance on pension contributions, wellbeing, gym and fitness, education, childcare and more 
  • 22 days holiday per year, plus National Bank Holidays (or a day in lieu) 
  • An industry-leading referral scheme, with no limits on the number of referrals 
  • Hybrid working - Our roles are not fully remote as we take pride in the tight knit communities we have created at our local offices. But we offer plenty of flexibility and you can split your time between the office, client site and WFH
  • We also help you setting up your home office to make sure you’re comfortable with hybrid working 
  • Training opportunities and incentives – we support professional certifications across engineering and non-engineering roles, including unlimited access to O’Reilly 
  • You will become part of a squad with people from different areas within the business who will help you grow at BJSS 
  • Giving back – the ability to get involved nationally and regionally with partnerships to get people from diverse backgrounds into tech 
  • BJSS Clubs: From trekking and paddle to books and board games, BJSS is keen on sponsoring various group activities among our employees 

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