Data Solutions Engineer
2 months ago
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 (, 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 (, Pandas) is a plus. Passion for AI and ML technologies, with a history of exploring new concepts and techniques.-
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