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Machine Learning Engineer
2018-06-26 19:27:44| Space-careers.com Jobs RSS
Vacancy in the Directorate of Earth Observation Programmes. ESA is an equal opportunity employer, committed to achieving diversity within the workforce and creating an inclusive working environment. Applications from women are encouraged. Post Machine Learning Engineer This post is for a limited duration of 4 years, nonrenewable, and is classified A2A4 on the Coordinated Organisations salary scale. Location ESRIN, Frascati, Italy Description Machine Learning Engineer in the lab Explore Office, Lab Division, Future Systems Department, Directorate of EO Programmes Duties The postholder will report to the Head of the lab Explore Office. Working in an open, collaborative, multidisciplinary team lab, in active cooperation with other staff of the Directorate and ESA, as well as in cooperation with industry and research communities in the framework of ESA programmes, the postholder will Conceive, rapidly prototype, and evaluate machinelearning solutions for application to Earth observation EO data sets and challenges, particularly those relevant to ESA EO missions Adapt existing Machine Learning ML and Deep Learning DL algorithms and tools to take account of the specific characteristics of EO data sets, physical measurement principles, and metadata Prepare, validate and maintain largescale training data sets, to be used for development and evaluation of MLDL algorithms and challenges, by international research and industrial communities Initiate and prepare technical specifications and statements of work, and oversee small, focused, exploratory projects to be competitively tendered and executed by industry and research organisations in ESA Member States Collaborate with partners in academia, the private sector and the startup ecosystem to foster use of EObased solutions in their practices Provide ML technical support and guidance to the lab team Technical competencies Computer science fundamentals Application of statistical analysis methods to multidimensional data sets Probabilistic modelling and validation for large observational data sets Applying MLDL algorithms to EO and Geospatial data Software engineering and system design for Machine Learning Behavioural competencies Innovation Creativity Problem Solving Self Motivation Education A Masters degree or equivalent in relevant disciplines, e.g. engineering, computer science, applied physics Additional requirements Programming in several of Python, R, JavaScript, CC Deep learning tools such as Tensorflow, Caffe, PyTorch Research record in the MLDL field Knowledge of geospatial big data analytics techniques 3 years industrial experience is required. Other information For behavioural competencies expected from ESA staff in general, please refer to the ESA Competency Framework. The working languages of the Agency are English and French. A good knowledge of one of these is required. Knowledge of another Member State language would be an asset. The Agency may require applicants to undergo selection tests. The closing date for applications is 31 July 2018. If you require support with your application due to a disability, please email contact.human.resourcesesa.int. Please note that applications are only considered from nationals of one of the following States Austria, Belgium, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Luxembourg, the Netherlands, Norway, Poland, Portugal, Romania, Spain, Sweden, Switzerland, the United Kingdom and Canada and Slovenia. According to the ESA Convention the recruitment of staff must take into account an adequate distribution of posts among nationals of the ESA Member States. When shortlisting for an interview, priority will first be given to external candidates from underrepresented Member States. In view of the limited duration of this post, internal candidates are strongly advised to contact their HR advisor before applying. see Nationality Targets In accordance with the European Space Agencys security procedures and as part of the selection process, successful candidates will be required to undergo basic screening before appointment. Recruitment will normally be at the first grade in the band A2 however, if the candidate selected has little or no experience, the position may be filled at A1 level. Apply HERE
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