Machine Learning Engineer

We're a Data team. We gather specialists passionate about data, our mission is to help grow Eneba's organization as a data-driven decision-maker by providing a solid data foundation. We want to foster a healthy data culture across the organization and enable our colleagues to have easier access to the necessary data that they require in their day-to-day activities. Our team gathered ML experts who are creating amazing machine-learning models. Data Analysts provide crucial data insights for teams and Data Engineers who build cutting-edge data pipeline solutions.

Responsibilities

• Collaborate with cross-functional teams to translate business requirements into technical solutions.

• Partner with Data Engineers to design and maintain automation for machine learning training, quality assessment, and model release process.

• Implement MLOps practices like CI/CD pipelines and model deployment using appropriate tools and frameworks.

• Stay up to date with industry trends and incorporate new tools or technologies as seen fit.

• Provide technical leadership by mentoring team members and contributing to technical discussions.

Requirements

• 3+ years of experience in ML engineering or in a similar role.

• Extensive experience working with Python.

• Strong understanding of Machine Learning algorithms.

• Experience with Deep Learning frameworks such as PyTorch, TensorFlow, or Keras.

• Experience with MLOps tools like MLflow or similar platforms for model lifecycle management.

• Familiarity with Databricks would be a significant advantage.

€55,000 - €74,000 a year

*Salary ranges may vary. We’re seeking candidates with varied experience levels; from individual contributors to functional leaders in this space.

*We’re an international team and our business language of choice is English. Good English level is required, proficiency is preferred.

What it’s like to work at Eneba

• Opportunity to join our Employee Stock Options program.

• Opportunity to help scale a unique product. 

• Various bonus systems: performance-based, referral, additional paid leave, personal learning budget.

• Paid volunteering opportunities.

• Work location of your choice: office, remote, opportunity to work and travel.

• Personal and professional growth at an exponential rate supported by well-defined feedback and promotion processes. 

• Please attach CV's in English.