Operations Solution Engineer
3 weeks 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.
- 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.
- 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 (e.g., 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 (e.g., 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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