Senior Engineer - Backend & Machine Learning

• What’s my job title? Senior Machine Learning Engineer
• Where in the world? You can work remotely from anywhere in the European Union. Ideally in the Netherlands, Spain, Portugal or the UK. 
• Working hours? For this role, you will operate within Central European Time (CET)
• What language(s) will I speak? Fluency in English

As Senior Machine Learning Engineer you’ll be responsible for research, design, development and maintenance for both our internal and customer-facing machine learning services. You will play a vital role in translating real-life customer problems into scalable and easy-to-use solutions. You will not only throw models over the fence, but also give valuable input to designers and FE'ers how to build UX in such a way that ML is accessible for any customer.What You’ll Do

What You’ll Do

• Help research, design, develop, deploy and maintain our production machine learning services
• Innovate, improve and operate our core and foundational services supporting all our development teams on applications and customer facing products
• Curate and collect data: develop and acquire datasets representative of core customer use cases
• Grow the ML team vision by continuously sharing knowledge and staying up to date with current developments in the field
• Problem-solve issues based on business/customer needs and impact, working with technical and non-technical stakeholders.
• You will flourish working in a hyper-growth environment where the next project is ready to be picked up

What You’ll Bring

• Significant experience in deploying large-scale production grade applied machine learning systems.
• Exceptional knowledge of production-ready and modern Python.
• Experience with Golang and/or Protobuf.
• Experience in data collection, data cleaning, data visualisation.
• Background in Machine Learning, Data Science + Engineering or related fields.
• Knowledge in data structures, algorithm design and complexity analysis.
• Familiarity with statistics and probability and linear algebra.
• Strong knowledge of TensorFlow, Pytorch, or any other ML framework.
• Experience with microservices and highly distributed cloud based systems.
• Self-sufficient with a strong sense of ownership.

Bonus Points

• DevOps experience in cloud infrastructure management with tools like Terraform, Serverless, or AWS CDK.
• Practical and theoretical knowledge of development patterns, software architectures and design patterns (TDD, Event-Driven, SOLID, Hexagonal, DDD).
• Knowledge of (cloud) infrastructure principles (load balancing, high availability, containerized services, database configurations).
• Strong experience working with relational and non-relational data stores (like Postgres, DynamoDB & Redis).
• Experience with Amazon Web Services including ECS, S3, SNS, SQS, and Lambda.
• Experience with Docker and containers.

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