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Machine Learning Engineer

Remote:

Full Remote

Contract:

Full time

Experience:

Mid-level (2-5 years)

Work from:

Republic of Lithuania

Offer summary

Qualifications:

3+ years of experience in ML engineering, Extensive experience with Apache Spark and Python, Strong understanding of machine learning algorithms, Experience with ML frameworks like TensorFlow, PyTorch, Familiarity with MLOps tools like MLflow.

Key responsabilities:

Collaborate with teams to meet business requirements
Design and maintain automation for ML processes
Implement MLOps practices and model deployment
Stay updated on industry trends and technologies
Mentor team members and lead technical discussions

Eneba Scaleup https://www.eneba.com/

51 - 200 Employees

See more Eneba offers

Job description

About Eneba

We’re building an open, safe and sustainable marketplace for the gamers of today and tomorrow. Our marketplace supports more than 10m+ active users (and growing fast!), provides a level of trust, safety and market accessibility unparalleled to none. We’re proud of what we’ve accomplished in such a short time and look forward to sharing this journey with you. Join us as we continue to scale, diversify our portfolio, and grow with the evolving community of gamers.

About your team

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 with Apache Spark using Python for large-scale data processing.

Strong understanding of machine learning algorithms.

Experience with ML frameworks such as sci-kit-learn, TensorFlow, PyTorch, or Keras.

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

Familiarity with Databricks would be a significant advantage.

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.

*To find out about how we handle your personal data, make sure to check out our Candidate Privacy Notice https://www.eneba.com/candidate-privacy-notice