Offer summary

Qualifications:

Strong experience in building end-to-end ML pipelines, including ETL, feature engineering, model training, deployment, and monitoring., Proficiency with AWS services such as Sagemaker, Glue, and Lambda., Hands-on experience with ML Flow, Spark, and Airflow., Effective collaboration and communication skills with data science teams..

Key responsibilities:

Build and maintain scalable ML pipelines covering all stages from data processing to deployment.

Leverage AWS and other technologies to develop robust ML solutions.

Collaborate proactively with data science teams and stakeholders to improve ML operations.

Employ development methodologies like TDD, DDD, and Agile Scrum to ensure quality and efficiency.

Job description

SUMMARY:

As a Data / ML Engineer, you'll be responsible for building and enhancing production Machine Learning solutions. You will collaborate closely with teams to develop robust, scalable data and ML pipelines, leveraging specified technologies and best practices.

WHAT WILL YOU BE DOING

Machine Learning Pipelines: Build and maintain end-to-end ML pipelines covering ETL processes, feature engineering, model training, deployment, serving (batch and inference APIs), and monitoring.
Tech Stack Utilisation: Leverage technologies such as AWS Sagemaker, AWS Glue, AWS Lambda, ML Flow, Spark, Airflow, and the Great Expectations Framework.
Collaboration: Proactively collaborate with data science teams and stakeholders to improve ML operations and processes continuously.
Development Practices: Employ methodologies such as Test-Driven Development (TDD), Domain-Driven Design (DDD), Agile Scrum, and foster effective data science collaboration.

WHAT WE ARE LOOKING FOR:

Strong experience building end-to-end ML pipelines (ETL, feature engineering, model training, deployment, serving, and monitoring).
Proficiency with AWS technologies, including Sagemaker, Glue, and Lambda.
Hands-on experience with ML Flow, Spark, and Airflow.
Effective collaboration and communication skills, particularly with data science teams.

AWESOME BUT NOT REQUIRED:

Experience with Google Vertex AI.
Familiarity with the Great Expectations Framework for data quality.
Proven experience working in Agile Scrum environments and practising TDD and DDD.

WHAT’S IN IT FOR YOU?

Be part of our collegial environment where responsibility and authority are shared equally amongst colleagues and help create our company culture
A culture in which we don’t criticise failure but ensure we learn from our mistakes
An Agile environment where your ideas are welcome
The possibility to grow and experience different projects
Ongoing Training & Mentoring
The possibility to travel

- ATTENTION! THIS POSITION IS FOR PORTUGAL OR BRAZIL BASED ONLY

Required profile