Work on functional design, process design (including scenario design, and flow mapping), prototyping, testing, training, and defining support procedures, in collaboration with an advanced engineering team and executive leadership.
Fine-tune a large language model using custom content (documents, data, etc)
Articulate and document the solutions architecture and lessons learned for each exploration and accelerated incubation.
Requirements & Skills:
9 or more years of experience in applying AI and machine learning techniques to practical and comprehensive technology solutions.
Proficiency in programming languages such as Python, and Rust.
Expert in ML, deep learning, TensorFlow, Python, NLP, and Transformer architecture.
Experience in deploying LLMs, and embedding model/sentence transformers in production use cases.
Deep understanding of Gen AI paradigms such as Retrieval Augmented Generation (RAG) architecture and prompt engineering techniques.
Demonstrated expertise in natural language processing, machine learning, and statistical analysis.
Thorough knowledge of basic algorithms, object-oriented and functional design principles, and best-practice patterns
Experience in REST API development, NoSQL database design, and RDBMS design.
Experience in fine-tuning a large language model using custom content (documents, data, code).
Passion for technology and a commitment to staying abreast of industry trends and advancements.
Experience with full-stack engineering and microservices architecture.
Good understanding of Distributed systems, design, and architecture.
Experience with offline experimentation and A/B testing.
Build, train, evaluate, and optimize deep learning models using PyTorch, Keras
Understanding of application development frameworks like LangChain, and LlamaIndex, and knowledge of vector index, and vector databases.
