Overview
Senior Manager, Global Talent Acquisition - Corporate at Welocalize. Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences with multilingual content transformation services in translation, localization, and adaptation for 250+ languages and a network of in-country linguistic resources. The company delivers 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 global clients in the markets that matter to them. www.welocalize.com
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 stakeholdersMentorship : Guide junior team members and contribute to a collaborative team environmentQualifications
EssentialsExcellent, in-depth understanding of machine learning concepts and methodologies, including supervised and unsupervised learning, deep learning, and classificationHands-on experience with natural language processing (NLP) techniques and toolsAbility to write robust, production-grade code in PythonExcellent communication and documentation skills. Able to explain complex technical concepts to non-technical stakeholdersExperience taking ownership of projects from conception to deployment. Ability to transform business needs to solutionsNice to haveExperience using Large Language Models in productionHigh proficiency with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learnHands-on experience with AWS technologies including EC2, S3, and other deployment strategies. Experience with SNS, Sagemaker a plusExperience with ML management technologies and deployment techniques, such as AWS ML offerings, Docker, GPU deployments, etcEducation and Experience
Master's Degree in Computer Science, Mathematics, Engineering, or similar field5+ years experience as a Machine Learning Engineer or similar role#J-18808-Ljbffr