System Engineer – Networking

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Descripción del trabajo

We are looking for a Senior Machine Learning Engineer to lead data-related initiatives and be a technical referent for the team. If you have a proficient background in information technology with a specific focus on ML and DL related to Data Science / Engineering, apply for the role and grow with us!

Your Responsibilities

• You design and build ML services to power our data products enabling data-driven decisions to improve traffic safety and prediction accuracy.
• You develop, train and test ML models to perform information retrieval and forecast analysis for mobility and traffic data domain.
• Using large data-sets to develop algorithms capable of learning and eventually making predictions.
• Analyzing use cases of ML algorithms, ranking by success probability and applying the outcome to support business decisions.
• Enriching existing ML frameworks and libraries.
• You productize training models and package them into independent software services.
• You continuously improve deployed models by applying state-of-the-art techniques as well as code and data set quality, you are automating what is not.
• Contribution to software development in close collaboration with the team.

Your profile

• Bachelor Degree / Master Degree / PhD in Computer Science, Maths, Physics or related.
• At least 7 years of experience in data related field with special focus on productizing AI solutions.
• Solid knowledge of Machine Learning and Deep Learning field, experience in building up machine learning train and release pipelines.
• Experience with probabilistic models and classification models.
• Hands-on experience with tools like Tensorflow, Keras, XGboost, Scikit-learn, Pytorch, autoML.
• Solid experience with Python.
• Knowledge of SCRUM / SAFe methodology.
• Experience with cloud.
• Analytical mindset and solution driven personality.
• You practice and live the agile mindset.
• Good oral and written English.

Our offer:

• A market compliant gross salary in line with your qualifications and your job experience.
• Permanent role.
• Flexible working hours.
• Hybrid working model (3 days of remote work / week).
• 30 business days of annual leave.
• Flexible remuneration plan: transport card, restaurant card, private medical care, etc.
• Challenging the limits of mobility for a healthy world without congestion.
• A hands-on onboarding with an experienced team in an international working environment.
• Ongoing professional education and training measures.