- Lead the development and implementation of our Tech Copilot chatbot, including prompt engineering, Retrieval-Augmented Generation (RAG) optimization, and model fine-tuning.
- Implement PEFT techniques such as LoRA and QLoRA to fine-tune models for efficient adaptation while minimizing computational resources and memory usage.
- Design, develop, and deploy brand new AI/ML models and algorithms to enhance product functionality, customer support, and overall user experience.
- Collaborate with cross-functional teams, including data scientists, software engineers, and subject matter experts, to integrate AI solutions into existing products and workflows.
- Optimize transformer-based architectures and enhance the accuracy of AI-generated responses through RAG systems.
- Develop and refine evaluation metrics and processes for continuous improvement of AI models and systems, including the implementation of MLOps practices.
- Fine-tune open-source and closed-source models, ensuring they are evaluated for performance and meet real-world application requirements.
- Stay abreast of the latest advancements in AI/ML, particularly in areas such as natural language processing and large language models.
- Contribute to the development of AI strategies and roadmaps for future initiatives across various business units.
- Align AI systems with data privacy regulations and implement standard methodologies for responsible AI development.
- Present complex AI concepts and project progress to a wide range of collaborators through presentations and reports.
- Relevant work experience in AI/ML development, with a focus on NLP and conversational AI.
- BS/MS in Computer Science, Artificial Intelligence, or a related field, or equivalent experience.
- Strong programming skills in Python, with experience in AI/ML frameworks such as PyTorch, TensorFlow, or JAX.
- Demonstrated experience with large language models, prompt engineering, LoRA, and QLoRA fine-tuning techniques.
- Proficiency in cloud computing platforms (preferably Azure) for AI model deployment and scaling.
- Experience with MLOps practices, including version control systems (e.g., Git), CI/CD pipelines, and monitoring tools for AI model deployment.
- A passionate AI engineer with a strong foundation in machine learning, natural language processing, and software engineering.
- Experienced in developing and deploying production-grade AI systems, particularly conversational AI and chatbots.
- Proficient in implementing and optimizing large language models, transformer architectures, and PEFT techniques such as LoRA and QLoRA.
- Skilled at fine-tuning models with fewer resources while maintaining high performance,
applying techniques like low-rank adaptation and quantization.
- Comfortable working in cross-functional teams and translating business requirements into technical solutions.
Preferred Qualifications that Set You Apart:
- Familiarity with AI model evaluation metrics, A/B testing methodologies, and experiment tracking tools like MLflow.
- Knowledge of data structures, algorithms, and software design principles.
- Excellent problem-solving skills and attention to detail.
TBD