Senior AI Engineer
LuxoftRomania2 days ago
Full-timeBusiness Development
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Project Description (VR-118175):
- We are seeking an experienced Data Scientist / AI Engineer to join our team as a contractor. The successful candidate will work on developing a state-of-the-art NLP assistant for a large financial software platform. This role will involve leveraging cutting-edge Generative AI technologies to create innovative solutions for data extraction, API integration, automated report generation, and more. The ideal candidate will have a strong background in data science, machine learning engineering, and prompt engineering.
- Responsibilities:
- • Implement NLP Solutions: Utilize NLP models to develop features for a financial software platform using Python.
- • Prompt Engineering: Create, refine, and optimize prompts for generative AI models to achieve desired outputs for various financial use cases.
- • Data Extraction: Build systems to extract relevant data from databases using NLP techniques and integrate this data into workflows.
- • API Integration: Develop and maintain integrations with various APIs to enhance the capabilities of the NLP assistant.
- • Automated Report Generation: Utilize generative AI to automate the creation of detailed and accurate financial reports.
- • Collaboration and Communication: Work closely with software engineers, business analysts, and other stakeholders to understand requirements and deliver high-quality solutions.
- • Continuous Improvement: Stay up to date with the latest advancements in NLP and generative AI to continuously improve the assistant's capabilities.
- Mandatory Skills Description:
- Education: Degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or a related field, with a strong emphasis on AI and machine learning.
- Experience: Proven experience in data science, machine learning engineering, and NLP.
- Technical Skills:
- o Proficiency in Python and experience with data science libraries
- o Experience with prompt engineering and fine-tuning large language models
- o Experience in LangGraph and LangChain
- o Familiarity with SQL.
- o Experience with Model Context Protocol (MCP) standard
- o Experience with Text-to-SQL (NL2SQL)
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