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Machine Learning Engineer
Welocalize
Cluj-Napoca, Romania
View more jobs at Welocalize
As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

MAIN PURPOSE OF ROLE

As a Machine Learning Engineer, you will provide the machine learning/data science expertise necessary for the NLP Engineering team and will play a crucial role in the development and implementation of cutting-edge approaches and tools for content translation, analysis and linguistics-based processes. This includes designing and developing machine learning systems, implementing appropriate ML algorithms, and staying updated with the latest developments in the field.

MAIN DUTIES

    • The following is a non-exhaustive list of responsibilities and areas of ownership of the Machine Learning Engineer:
    • Keep familiar with state-of-the-art machine learning/data science approaches applicable to the field of natural language processing (NLP): 
    • Neural machine translation (NMT)
    • Data curation & text classification tasks
    • Investigate new research directions and their potential for novel, practical application to NLP-related tasks
    • Quality estimation and evaluation
    • Act as educator and ambassador for ML in the field of NLP (internal training, conference presentations/workshops, papers, blog articles)
    • Improve existing NLP approaches including:
    • Practical proprietary neural MT implementation (OpenNMT BRNN, transformer models, etc.)
    • Data selection and augmentation, domain adaptation, named entity recognition (NER), terminology extraction, quality estimation, and document classification
    • Language-specific techniques (e.g., morphological analysis, syntax-based approaches)
    • Define/refine best practices when developing translation solutions and engines for new language pairs, domains/topics and content types
    • Work with the software engineering team to turn research techniques into practical commercial solutions
    • Work on broader considerations of practical MT use, e.g. file processing, tag handling, data cleaning, and translation efficiency
    • Lead the implementation of end-to-end projects for new client
    • Develop tools that help streamline workflows and productivity for both internal and external customer

REQUIREMENTS

    • Education 
    • Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science or similar discipline (or equivalent experience)
    • Technical Skills and Experience
    • Commercial experience in machine learning and/or NLP/computational linguistics
    • Strong knowledge of core NLP approaches
    • Knowledge of latest trends in Machine Learning & Artificial Intelligence
    • Strong programming skills (Python preferred)
    • Proficiency working within a Linux environment
    • Desirable Technical Skills and Experience 
    • Hands-on experience working and developing with common NLP & ML packages
    • NLP experience with a language other than English
    • Experience with Docker or similar virtualization platform Familiarity with tools and processes in a localization workflow such as translation management tools, post-editing, and translation evaluation
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Full-time
Mid Level
Natural Language Processing