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XE is looking for an experienced ML and data Engineer to join the XE Data Science team.

As an ML and data Engineer you’ll be responsible for designing, building, and maintaining the infrastructure and processes required to successfully deploy and manage machine learning models in a production environment. This includes tasks such as building and maintaining a feature store, delivery pipelines, automating model training and evaluation, and monitoring model performance.

The role will work closely with data scientists and software engineers to ensure that machine learning models can seamlessly integrate into existing systems and processes. The role will also be responsible for identifying and implementing best practices for managing and optimizing machine learning models in production.

The ideal candidate for this role will have a strong experience in both software engineering and machine learning, as well as a deep understanding of the challenges and best practices involved in deploying machine learning models in production. Having experience working with cloud computing platforms such as AWS or GCP is a plus.

Please note until office restrictions are relaxed, you will be working remotely.

Our principles

  • AMBITION - We dream big, try things out and always ask “why not?” and “what if?” We’re ambitious in our thinking and our delivery
  • RESPONSIBILITY - We get involved, bring our perspective and are always open to new ideas. We take personal responsibility
  • COMMUNITY - We value a sense of belonging, trusting each other and encouraging authenticity. We contribute to our community

Requirements

What You'll Be Doing:

  • Machine Learning Expert: Build and maintain real-time machine learning features using production level programming techniques
  • Manage the Creative Process: Design, develop, and maintain a central feature store
  • Process Oriented: Automate the training, evaluation, and deployment of machine learning models
  • Monitor and Optimize: The performance of machine learning models in production
  • Collaboration: Work closely with data scientists and software engineers to ensure the successful integration of machine learning models into existing systems and processes
  • Identify and Implement Best Practices: For managing and optimizing machine learning models in production
  • Build and maintain production level real-time and batch MLOps pipelines.
  • Design, develop and maintain ML Entity Resolution service.
  • Design and develop multiple ML microservices and APIs.

Requirements:

  • Degree in Computer Science, Software Engineering, or related discipline
  • Strong knowledge of developing and maintaining API services in a cloud environment
  • Strong object and service-oriented programming skills in Python to write efficient, scalable code
  • Knowledge of modern containerization techniques - Docker, Docker Compose
  • Experience with relational and unstructured databases and data lakes
  • An understanding of business goals and how data policies can affect them
  • Effective communication and collaboration skills
  • A strong understanding of the concepts associated with privacy and data security

Benefits

1. Annual salary increase review

2. End of the year bonus (Christmas bonus)

3. ESPP (Employee Stock Purchase Plan)

4. Paid day off for birthday

5. 15 day vacation per year

6. Insurance guaranteed for employees ( Health, Oncological , Dental , Life Insurance)

7. No fee when using RIA service/wire transfers

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