Machine Learning R&D Engineer

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 languages with a growing network of over , 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. 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. Job Reference : #LI-JC1 Role Summary : The Machine Learning R&D Engineer role is responsible for the design, development and implementation of machine learning solutions to serve our organization. This includes ownership or oversight of projects from conception to deployment with appropriate AWS services, Docker, MLFlow, and other. The role also includes responsibility for following best practices with which to optimize and measure the performance of our models and algorithms against business goals.

Tasks and Responsibilities :

• Machine learning model research and development :  design, develop and deploy machine learning models for localization and business workflow processes, including machine translation and quality assurance. Utilize appropriate metrics to evaluate model performance and iterate accordingly.
• Ensure code quality :
• Write robust, well-documented, and structured Python code.
• Define and design solutions to machine learning problems : Work closely with cross-functional teams to understand business requirements and design solutions that meet those needs. Explain complex technical concepts clearly to non-technical stakeholders.
• Mentorship : Guide junior team members and contribute to a collaborative team environment.

Success indicators of a Machine Learning R&D Engineer :

Skills and Knowledge

Nice to have :

Education and Experience