Machine Learning Engineer

Nicosia, Nicosia, Cyprus

Plum

Plum is the ultimate smart money app, helping over 1 million people to invest, save and manage their spending with automation.

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At Plum, we're on a mission to maximise wealth for all. We’re making saving money effortless and turning investing into something everyone can do.

Our journey began back in 2017, when we became one of the first to use artificial intelligence and automation to simplify personal finance. Fast forward to today, and we've already helped people save £2 billion across 10 European markets.

Named the UK's fastest-growing fintech in the Deloitte Technology Fast 50, our success is down to the passion and dedication of our diverse team. Based in our London, Athens and Nicosia offices, 170 talented people work together to empower people to do more with their mone. And now, the team is growing!

About the Role

We are looking for a talented and passionate Machine Learning Engineer to join our team and build the next generation of our real-time, data-driven applications. As a Machine Learning Engineer, you will provision and expand the infrastructure of ML and AI at Plum, whilst collaborating closely with Data Engineers and Data Scientists, who are currently managing numerous live production ML systems and delivering on a substantial roadmap. This traverses areas such as document processing automation, transaction fraud detection, marketing spend optimisation and customer retention.

What will you do

  • Collaborate with data scientists, data analysts and data engineers on production systems and applications focused on traditional ML, generative AI and MLOps
  • Transition ML models from experimental prototypes to production deployments that can handle high volumes of data in real-time, enabling us to make rapid decisions and provide immediate value to our users
  • Stay engaged with the latest advancements in data science and fintech, particularly in the areas of leveraging ML techniques to deliver business impact.
  • Contribute to the continuous development of our AI and ML Ops infrastructure, covering areas such as model deployment, continuous retraining, feature store, performance monitoring and drift detection.
  • Exercise software engineering best practices in the codebase, like version control and continuous integration, with an aim to ensure our models are not just effective, but also thoroughly tested, well-documented, and regularly maintained.
  • Promote a culture of mutual learning and growth, where teaching and learning from colleagues is encouraged. We highly value knowledge sharing and ongoing learning.

Who you are👀

  • Strong foundations in data structures, data modelling (e.g. Airflow and dbt), software architecture, Python, SQL, machine learning frameworks (e.g. Keras, PyTorch), and libraries (e.g. scikit-learn).
  • Proven experience in developing, maintaining and deploying machine learning models for real-time applications, with a strong understanding of streaming data processing technologies and real-time inference frameworks in production environments
  • Strong understanding of ML applications development life cycle processes and tools: CI/CD, version control (git), testing frameworks, MLOps, agile methodologies, monitoring and alerting, experiment trackers (e.g. mlFlow) & orchestrators (Airflow, Kubeflow)
  • Experience in building and optimizing scalable machine learning infrastructure in a cloud setup. We use Google Cloud Platform and leverage services like BigQuery, Vertex AI, and Cloud Storage.
  • You have a solid understanding of how to measure the performance of ML models
  • Strong problem-solving skills, a critical and creative mindset, and a team-oriented approach with a focus on mentorship and knowledge sharing.

Nice to Have

  • Deep knowledge of math, probability, statistics and algorithms
  • Experienced with Large Language Models, Generative AI, Langchain, Transformer models
  • Understanding of the concepts of GPU-powered workloads, NVIDIA drivers, container runtimes
  • Experience provisioning infrastructure components using Terraform, including virtual machines, storage, databases, and other necessary services

Plum's Perks

  • We're all in this together! Own part of the company through stock options 💷
  • Annual training budget
  • Private Life Insurance - Ethniki Asfalistiki
  • Provident Fund - Ancoria Bank
  • Free Plum Premium subscription (normally £9.99 a month).
  • Free parking slots
  • 25 days holiday a year, excluding public holidays
  • Employee referral scheme up to €4000
  • Flexible approach to remote working, though we encourage at least 2-3 days a week in our beautiful office in Nicosia for optimal collaboration.
  • 45 days work from anywhere
  • Team lunch on Thursdays in the office, as well as a plentiful supply of fruit, snacks and coffee.
  • 1 day paid leave for volunteering, supporting you giving back to society.
  • 2 weeks paid sabbatical after four years of service.
  • Team trip to secret destinations once a year ✈️
  • A vibe that’s 🦄🌈💯

If you think this sounds like a bit of you then don’t hesitate to get in touch!

Thanks,

Plum Τeam 💜

*Plum is an Equal Opportunity Employer. Plum does not discriminate on the basis of age, race, religion, sex, gender identity, sexual orientation, non-disqualifying physical or mental disability, national origin or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit and business need.Plum's Perks

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Agile Airflow Architecture BigQuery CI/CD dbt Engineering Finance FinTech GCP Generative AI Git Google Cloud GPU Keras Kubeflow LangChain LLMs Machine Learning Mathematics MLFlow ML infrastructure ML models MLOps Model deployment Python PyTorch Scikit-learn SQL Statistics Streaming Teaching Terraform Testing Vertex AI

Perks/benefits: Career development Equity / stock options Flex hours Insurance Paid sabbatical Snacks / Drinks Startup environment Travel

Region: Middle East
Country: Cyprus

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