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Machine Learning Senior​/Staff Engineer

Online/Remoto - Ideal para candidatos en
08001, Barcelona, Cataluna, España
Empresa: Smadex
Tiempo parcial, Remoto/Desde casa puesto
Publicado en 2026-02-17
Especializaciones laborales:
  • TI/Tecnología
    Machine Learning, Científico de datos, Analista de datos, Ingeniero de datos
Rango Salarial o Referencia de la Industria: 50000 - 70000 EUR Anual EUR 50000.00 70000.00 YEAR
Descripción del trabajo

Smadex is a leading advertising technology company founded in Barcelona in 2011 and sold to American‑based, stock‑listed Entravision in 2018 (NYSE::

EVC). We are one of the top mobile ad‑tech companies in the world and the largest Demand Side Platform (DSP) based in Europe, with revenues over +$100M and consistently growing +40% YoY over the past years.

Our mission is to continue to improve our ad‑tech platform to help our clients achieve their programmatic advertising campaign goals, and we want to give our employees a job they’ll love, where they will be challenged to improve results through real‑life engineering and data analysis and where everyone’s implication has an impact.

Are you ready to be part of the new unicorn? Keep reading!

What will you do:
  • As a Machine Learning Senior/Staff Engineer you will be part of all the major architectural decisions and developments we make on our algorithms, especially in our deep neural network algorithms.
  • You will be responsible for developing new features, measuring the performance and improving our pipelines. Our ML Engineer role combines the classic “ML Scientist” and “Data Engineer” role at other companies.
  • You will also play an analytical role researching, designing, implementing, and deploying full‑stack scalable data analytics and machine learning solutions to challenge business issues, as well as working closely with our Tech and Ops team.
  • You will work on unique modeling challenges not covered in the scientific literature, like extreme positive sample sparsity and labelling delay.
  • Analyze data from different sources and provide actionable insights to business and engineering stakeholders.
What you need to have:
  • 5+ years of relevant experience in Data science positions.
  • Very strong coding ability:
    Python, Scala, Java.
  • Proficiency in building high‑performance algorithms in production.
  • Proficiency in solving problems.
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical significance tests).
  • Experience in data mining and predictive modelling: deep neural networks, logistic regression, clustering and time series analysis models.
  • Knowledge of Bitbucket/Git version tools.
  • Experience working with SQL and data warehousing.
  • Possesses excellent communication skills both verbal and written.
  • Able to mentor other team members.
  • Fluency in English.
Extra points for :)
  • Master’s degree in Statistics, Applied mathematics, Computer Science.
  • Proficiency in building high‑performance algorithms in production.
  • Experience with reporting and data visualization tools such as Jupyter Notebook, Zeppelin, Tableau, Periscope, Power

    BI or others.
  • Experience in digital marketing platforms and user acquisition.
  • Experience with and Apache Spark and Java programming language.
  • Familiarity with AWS services such as EMR, EC2, Athena, S3, Redshift.
  • Used to Linux environments.
Reward package:
  • Integrate a highly motivated and young team.
  • Great compensation package.
  • Top location at the heart of Barcelona in a penthouse office with a rooftop terrace, barbeque, and a fully stocked fridge.
  • Work from home: 2 days/week.
  • Private Health Insurance.
  • Access to Linked In Learning.
  • Meal vouchers – Tickets Restaurant monthly allowance.
  • Monthly gym allowance:
    Choose between DiR Gym and Wellhub.
  • Monthly TGIF events.
  • Regular team‑building events.
  • Fun and friendly work environment with talented marketers and engineers from over 40+ countries.
  • And more!
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Requisitos del puesto
10+ años Experiencia laboral
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