Data Deployment Engineer
3 days ago
These 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 and labeling to improve discovery/search results, model accuracy for sentiment analysis, sensitive content detection, and named entities. Data validation and classification. NLP Consulting.
Responsibilities
Collaborate with customers to understand their end goals, help define data and linguistic specifications, and accept protocols to enable the scoping of incoming AI projects. Manage the development and enhancement of AI enablement tools and NLP applications, as well as the creation of internal project specifications, linguistic guidelines, workflow instructions, and training content. Collaborate with the quality team to design and implement quality evaluation protocols, data spec compliance tools, and defect management strategies. Make fit-for-purpose work surface recommendations and work with internal product owners to advocate for features necessary to accomplish project goals. Communicate on project progress, address concerns or issues, and build strong relationships with clients. Coordinate with internal quality leads, project managers, linguists, and recruiters to ensure seamless project execution. Stay current with the latest trends and advancements in AI and NLP, proactively exploring new technologies and methodologies to enhance our services. Ability to manipulate and manage large data sets for file management across tools and platforms. Learn and manage internal tools. Gain proficiency in Pantheon, our internal tool, to manage financial reporting requirements, and integrations, and support project tracking within AI projects. Architect and propose client-facing technical solutions. Directly engage with clients to design and implement technical solutions that meet their specific AI and NLP needs.
Requirements
3-5 years of experience in technical or consulting roles, such as product management, engineering, or business analysis. Bachelor's degree in computational linguistics or an analytics-heavy field (, computer science, engineering, economics, statistics) or equivalent work experience. Front-end development experience (nice to have). Possessing front-end development skills to create and manage specialized web tools will be helpful in this role. Strong understanding of data structures. Demonstrate proficiency in data structures to optimize data handling and processing, essential for effective AI model training and data management. a proven track record in developing, deploying, and maintaining NLP models, with a strong understanding of NLP concepts and techniques. Hands-on experience in ML lifecycle applications, data management, data wrangling, and quality assurance for linguistic data. 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. Demonstrated ability to manage complex, cross-functional projects, influence customers, stakeholders, and collaborators, and communicate complex concepts effectively to non-technical audiences. Excellent communication and interpersonal skills, with a focus on managing client relationships. Passion for AI and ML technologies and a history of exploring new concepts and techniques.-
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