Compartir esta oferta de trabajo

Specialist Machine Learning Engineer

Fecha: 28-dic-2021

Ubicación: Madrid, ES

Empresa: Vodafone

We invite you to join Vodafone to build a future together, in a position where you can learn new things every day and have contact with the different business units of the Company, as well as related institutions and public bodies.


Machine Learning Engineers are responsible to manage and improve the performance of the AI/ML models implemented in the Big Data and AI department. From the data reliability and quality stages to the tracking and monitoring of the models in production the Modeling Engineers combine raw information from different sources to create consistent and machine-readable formats, develop and test architectures that enable data extraction and transformation for predictive or prescriptive modeling and build core infrastructure around model training, model deployment, ongoing monitoring tools, and much more. Their key responsibility is ensuring that the Big Data models are developed, implemented and continually improved with the maximum possible efficiency.


Machine Learning Engineer roles and responsibilities include:

  • Create and maintain optimal data pipeline architecture.
  • Assemble large, complex data sets that meet functional / non-functional business requirements.
  • Identify, design, and implement internal data modelling process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Work with Data Engineering to ensure the adequacy of the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Google Cloud ‘Big Data’ technologies.
  • Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
  • Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
  • Monitoring data quality and efficiency.
  • Study and transform data science prototypes.
  • Develop machine learning applications according to data scientists’ requirements.
  • Run machine learning tests and experiments.
  • Train and retrain systems when necessary.
  • Extend existing ML libraries and frameworks.
  • Deploying and scaling ML solutions.
  • Build and maintain a model performance tracking environment to ensure monitoring and alarming of the Big Data models in production to quickly identify and qualify any performance issues for continuous improvement of the models.


What you bring:

  • Graduated in Computer Science, Telecommunications Engineering, or related field.
  • Master’s in Big Data, Data Engineering, or any data related field, desired.
  • At least, 3 years of professional experience in Software Development/Data Engineering related positions.
  • English proficiency is a must.
  • Advanced knowledge and experience in Software Development (OOP, design patterns, anti-patterns, TDD)
  • Advanced knowledge and ability to write robust code in Python (decorators, PEP8, …)
  • Advanced knowledge and experience developing efficient pipelines with Spark (dataframes, map/reduce, lazy evaluation, caching, broadcasting, …)
  • At least, basic knowledge of SQL, and bash.
  • Experienced usage of Big Data technologies: Spark, Hadoop, Hive/Impala, Kafka, etc.
  • Hands-on experience with testing frameworks (PyUnit/Unittest, junit, …).
  • Experienced usage of Google Cloud technologies: Dataproc, Airflow, Dataflow, BigQuery, …
  • Experienced data management using different platforms: HDFS, Cassandra, Hive, HBase, etc.
  • Technical flexibility for adapting to the required technological and development environment depending on each use case.
  • Knowledge of agile methodologies (Scrum, sprints, backlog, …).


At Vodafone we are concerned about being a company committed to diversity as an engine of change. We are proud to offer equal opportunities regardless of race, nationality, cultural origin, sex, age, marital status, sexual orientation, gender identity, disability and religious or political beliefs.