REQUIRED SKILLS AND QUALIFICATIONS:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. A degree specializing in AI/ML is a significant plus. Ph.D. preferred.
• 10+ years of experience in AI/ML, with at least 3 years of specialized experience in Generative AI, including demonstrated success in deploying production-ready GenAI solutions, preferably with a focus on document processing.

TECHNICAL SKILLS:

• Programming Languages: Expert-level proficiency in Python.
• GenAI & LLM Frameworks: Deep understanding and hands-on experience with Transformers, LangChain, Llama 3, Llama 4, Gemini, GPT-4+, and other relevant libraries.
• Data Science & ML Libraries: Proficiency in NumPy, Pandas, SciPy, Scikit-learn, TensorFlow, PyTorch.
• RAG Pipelines & Vector Databases: Expertise in designing and implementing RAG pipelines using vector databases like Postgres, Pinecone, Weaviate, Faiss, and Chroma.
• Document Processing & NLP: Experience with PDF parsing libraries, chunking techniques, re-ranking algorithms, and table transformers. Strong NLP skills for text extraction, analysis, and understanding from documents.
• Database Technologies: Proficiency in SQL and dynamic SQL for relational databases (e.g., PostgreSQL, MySQL, SQL Server). Experience with NoSQL databases is a plus.
• Cloud Platforms & MLOps: Familiarity with major cloud providers (AWS, Azure, GCP) and MLOps tools like MLflow, Kubeflow, and CI/CD pipelines.
• Software Engineering: Strong understanding of software engineering principles, including version control (Git), testing, and code quality.

OTHER SKILLS:

• Excellent communication and collaboration skills.
• Knowledge of Agentic AI and other emerging trends in GenAI.
• Strong analytical and problem-solving abilities.

PREFERRED QUALIFICATIONS:

• Experience in the financial industry.
• Familiarity with specific GenAI applications in finance (e.g., algorithmic trading, risk management).
• Contributions to open-source projects.

EDUCATION:

• Bachelor’s degree/University degree or equivalent experience
• Master’s degree preferred
  This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
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MOST RELEVANT SKILLS

Please see the requirements listed above.
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OTHER RELEVANT SKILLS

For complementary skills, please see above and/or contact the recruiter.
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ABOUT THE ROLE:

We are seeking a highly skilled GenAI Tech Specialist to join our innovative team in Tampa, FL. This critical role will focus on driving AI/ML advancements within our finance division, with a particular emphasis on document processing and analysis. You will be responsible for the end-to-end integration of GenAI solutions, from understanding data requirements to collaborating with cross-functional teams and deploying production-ready applications. This role requires demonstrable experience in implementing real-world GenAI products, particularly those involving structured and unstructured data[database & documents].

RESPONSIBILITIES:

• Design, develop, and deploy production-ready GenAI solutions for various financial applications, such as risk assessment, fraud detection, personalized financial advice, and automated reporting, with a focus on leveraging document-based information.
• Work with both structured and unstructured financial data, including complex documents (PDFs, etc.), implementing techniques like NLP, information retrieval, and document parsing for data processing and analysis. Define and gather data requirements for GenAI model training and evaluation.
• Design and implement Retrieval Augmented Generation (RAG) pipelines, leveraging expertise in vector databases and prompt engineering, specifically for document retrieval and analysis.
• Develop and deploy chatbot solutions and other conversational AI interfaces, integrating them with existing financial systems and document processing workflows.
• Utilize dynamic SQL to interact with relational databases, extracting and manipulating data for integration into GenAI pipelines, including data extracted from documents.
• Write high-quality, well-documented, and testable Python code, adhering to best practices for software development.
• Evaluate and integrate emerging GenAI technologies and tools, including the latest LLMs like Llama 3, Gemini, and exploring emerging models like Llama 4. Stay abreast of advancements in Agentic AI and assess their applicability to financial use cases, particularly in document processing.
• Define and track key metrics to evaluate the performance and impact of GenAI solutions, especially those related to document processing accuracy and efficiency.
• Collaborate effectively with Model Risk Management (MRM), the AI Center of Excellence (COE), and other cross-functional teams to ensure successful integration and deployment of GenAI products.
• Collaborate closely with stakeholders to translate business needs into effective technical solutions using GenAI, with a focus on addressing document-centric challenges.
• Contribute to the development and maintenance of MLOps pipelines, ensuring the scalability and reliability of deployed models, including those used for document processing.