Lead the design, development, and deployment of advanced AI/ML models and algorithms to solve complex business problems
Develop and integrate the AI agents/solutions seamlessly with existing Contract Management Systems (CMS) and document repositories.
Lead the design and implementation of end-to-end Retrieval-Augmented Generation (RAG) pipelines to ground LLMs with up-to-date and authoritative external data.
Manage the entire data flow for RAG, including document chunking, metadata management, and generating high-quality vector embeddings using state-of-the-art embedding models.
Evaluate, select, and manage vector databases (e.g., Pinecone, Weaviate, Qdrant) and indexing techniques (e.g., HNSW) to ensure fast and accurate semantic search and retrieval.
Continuously iterate on the RAG components, including retrieval algorithms and prompt engineering strategies, to maximize the contextual relevance and quality of generated responses.
Provide technical leadership and mentorship to junior data scientists, fostering a culture of continuous learning and improvement
Drive the strategic planning and execution of data science projects, ensuring alignment with business goals and timelines
Collaborate with cross-functional teams, including engineering, legal, product management and business stakeholders, to define project requirements and deliver data-driven solutions
Develop and implement scalable data pipelines and workflows to support the end-to-end data science lifecycle
Evaluate and integrate new data science techniques, tools, and technologies to enhance the company’s data capabilities
Communicate complex analytical concepts and results to non-technical stakeholders through clear and compelling data visualizations and presentations
Ensure the robustness, scalability, and performance of deployed models, monitoring their impact and iterating as necessary
Champion best practices in data science, including data governance, model validation, and ethical AI considerations
Identify and prioritize opportunities for leveraging data to drive business growth and operational efficiency
Pioneer peer reviews and foster a culture of continuous improvement and learning
Bachelor''s Degree in Computer Science, Electrical Engineering, Computer Engineering, Software Engineering, Aerospace Engineering, Math or Physics or a technical field (such as CIS or IT) relevant to the essential functions of this job description AND a minimum of 5 years of relevant experience OR an equivalent combination of education and relevant experience
Excellent academics (cumulative GPA greater than or equal to 3.0 as a general rule)
Extensive experience using systems such as SQL, Python, or R
Strong expertise in machine learning frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch)
Proven hands-on experience in fine-tuning Large Language Models (LLMs) and deep understanding of their architectures (e.g., Transformers).
Strong experience designing and deploying RAG systems and building high-performance semantic search and retrieval pipelines.
Practical experience with vector embeddings and working with vector databases for production-grade applications.
Demonstrated expert knowledge in data analysis methods and tools
Demonstrated strong and effective verbal, written, and interpersonal communication skills
Must be team-oriented, possess a positive attitude, and work well with others
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