.Smadex is a leading advertising technology company founded in Barcelona in 2011 and sold to American-based and stock-listed Entravision in 2018 (NYSE::EVC).
We are currently considered one of the top mobile ad-tech companies in the world, competing with American-based Liftoff and Korean-based Moloco, both pre-IPO stage and averaging about $1000M in yearly revenues.
We compete in a highly advanced technology-driven industry where Machine Learning, Data Science and cutting-edge cloud-based big data architectures make all the difference in the company's growth.
We are looking for ambitious engineers whose ultimate motivation is to learn the most advanced technologies used in the ad-tech industry by the likes of Google and Facebook and to help us become the biggest mobile programmatic advertising platform in the world.
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.
Our algorithms are in the core of the company.
They estimate the probability of a user to perform an action after seeing an ad, same as Google does.
But this needs to be done in nearly real time, in less than 100ms, and this is happening several million times per second.
Are you ready to be part of the new unicorn?
Keep reading We are seeking a highly skilled and motivated MLOps Team Lead to oversee the deployment and monitoring of machine learning algorithms in production environments.
The ideal candidate will have a strong background in MLOps practices, experience with deploying and maintaining ML models, and the ability to lead a team of engineers specializing in Python programming.
This role requires a balance of hands-on technical expertise and leadership skills to guide the team in delivering reliable, scalable, and efficient solutions.
What will you do: Lead, mentor, and manage a team of MLOps engineers and Python developers.
Facilitate collaboration within the team and across other departments to ensure seamless integration of ML systems.
Design, implement, and maintain end-to-end pipelines for ML model deployment, monitoring, and lifecycle management.
Develop automated workflows for CI/CD in ML systems to ensure rapid and reliable deployments.
Implement robust monitoring and alerting systems for production ML models to ensure performance and reliability.
Troubleshoot issues in real-time and ensure high availability of deployed systems.
Collaborate with the machine learning team (ML) to manage model retraining and updating processes.
Write, review and maintain high-quality Python code for MLOps tooling and automation.
Evaluate and integrate state-of-the-art tools and technologies in the MLOps space