Airbus UpNext - Machine Learning Engineer (m/f) at AG | Torre
Airbus UpNext - Machine Learning Engineer (m/f)
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AG

Airbus UpNext - Machine Learning Engineer (m/f)

AG
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Full-time

Legal agreement: To be defined

USD75.4K - 100K/year

~COP150M - 200M/year

+ Equity

+ Bonuses

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Hybrid (Toulouse Area)
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Posted about 2 years ago

Requirements and responsibilities

Founded in 2017, Airbus UpNext is actively shaping the future of aerospace by using demonstrators to evaluate, mature and validate new products and services. Designed as a talent incubator, Airbus UpNext is a place where you can act and think like a startup while building on the strong expertise of Airbus, a place where you are empowered to challenge and test new processes and ways of working. The new Airbus UpNext demonstrator team is looking for a Machine Learning Engineer to assist the Development and Integration of ML algorithms into a Cloud Based Architecture. This position comes with a CDI-C contract for 3 years, the timeline of the demonstrator. The Project aims to further improve the autonomy and safety of aircrafts through the development and integration of new technical bricks. Among them are several functional concepts to provide assistance to the crew. Those functions will aim to help pilots during multiple aspects of flight, notably by reducing workload and offering optimization solutions. The Machine Learning Engineer will be responsible for handling Aircraft Operations datasets, identifying key parameters for desired functionalities, contributing to the development and prototyping of ML models for temporal prediction, and deploying said models in a cloud-based environment (Azure, AWS). The role also requires strong developer skills in C, C++, Python, knowledge of ML libraries (Tensorflow, PyTorch), experience with cloud services for ML and Data management (AWS, Azure), and aeronautical knowledge is a plus. Communication and collaboration skills, negotiation level in English, and a team-player mindset are essential. The position offers the opportunity to participate in the smart automations revolution, work in a shared open space office with highly skilled multicultural teams, craft a flexible calendar with the opportunity to work remotely, and participate in UpNext communities bonding events. The company values transparency, courage, humility, and empathy, and is committed to achieving workforce diversity and creating an inclusive working environment. Responsibilities: - Handle Aircraft Operations datasets and identify the key parameters for the desired functionalities - Contribute to the development and prototyping of ML models for temporal prediction - Deploy said models in a cloud-based environment (Azure, AWS)
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