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. Operations Solutions Engineer Welocalize’s fastest-growing service line is Welo Data, delivering a variety of AI data services to clients across the globe. We are partnering with customers across diverse industries to help them create, collect, annotate, and QA their training data to optimize AI and machine learning applications. Our AI data services encompass a wide range of solutions, including data generation, labeling, validation, and augmentation, enabling our clients to build, deploy, and improve their AI models effectively. Main Purpose The purpose of this Operations Solution Engineer role is to enable the delivery of high-quality AI data services to our clients, empowering them to harness the full potential of AI and NLP technologies in their operations. This role is pivotal to bridge the gap between Operations and customer needs, ensuring that our solutions are effectively implemented and optimized to meet client requirements. The Operations Solutions Engineer will leverage their applied experience and knowledge in developing AI modes to collaborate closely with our Operations team, driving project improvements, debugging issues, and launching new initiatives. At Welo Data, projects are consultative engagements designed to help our customers launch, improve, or maintain their ML models. This role will focus on ensuring that our AI data services align with client expectations and operational standards.
Example client projects might include:
Collecting training data and/or testing data for language models for deployment in multilingual conversational AI, search relevance, or other implementations.
Data Annotation/Labeling to improve discovery/search results, model accuracy for sentiment analysis, sensitive content detection, named entities.
Data validation and classification.
Responsibilities
Collaborate with the Operations team to understand customers' project goals, help define data specifications, and acceptance protocols to enable scoping of incoming AI projects.
Provide engineering support for the development and enhancement of AI enablement tools and NLP applications, ensuring that internal project specifications and workflows are successfully implemented.
Work with the quality team to design and implement quality evaluation protocols, data specification compliance tools, and defect management strategies to ensure high standards are met throughout the project lifecycle.
Make fit-for-purpose work surface recommendations and work with internal product owners to advocate for features necessary to accomplish project goals.
Stay current with the latest trends and advancements in AI and NLP, proactively exploring new technologies and methodologies to enhance our services.
Manipulate and manage large data sets for file management across various tools and platforms to support project needs.
Assist in architecting and proposing client-facing technical solutions, ensuring that the internal implementation aligns with client-specific AI needs, even without direct client interaction.
Requirements
2+ years of engineering experience, ideally in a client-facing setting
Bachelor's degree with a strong engineering background or an analytics-heavy field (e.g., Computer Science, Engineering, Mathematics, Statistics) or equivalent work experience.
Demonstrated proficiency in data structures to optimize data handling and processing, essential for effective AI model training and data management.
Hands-on experience in ML lifecycle applications, data management, and data wrangling.
Skills in front-end development for creating and managing specialized web tools would be a plus in this role.
A track record in deploying, and maintaining NLP models, with a strong understanding of NLP concepts and techniques would be a plus.
Proficiency in at least one scripting language, preferably Python.
Experience with programming languages, preferably C#.
Experience working with REST APIs
Experience with Jupyter or common data processing libraries (e.g., Pandas) is a plus.
Passion for AI and ML technologies, with a history of exploring new concepts and techniques.
