Responsibilities:

Fine-Tune and Customize Large Language Models (LLMs):

• Leverage your expertise in AI to fine-tune and customize LLMs for specific applications, including text generation, sentiment analysis, domain-specific tasks, audio-to-text transcription, and call center conversation insights.
• Develop and implement advanced prompting techniques to optimize LLM performance and ensure accurate, context-aware outputs.
• Conduct experiments to refine model performance, adjusting hyperparameters and data inputs to achieve the best possible results.

Develop and Implement Retrieval-Augmented Generation (RAG) Models:

• Design and develop RAG models that integrate vector databases for efficient information retrieval, enabling the creation of domain-specific chatbots and interactive AI solutions.
• Craft effective embedding, chunking, and indexing strategies to optimize RAG model performance and relevance.

AI Model Hosting and Deployment:

• Host, deploy, and scale AI models in production environments, ensuring they are stable, reliable, and capable of handling real-world demands.
• Utilize cloud platforms such as Azure AI Studio, OpenAI, and Snowflake Cortex to manage and monitor AI models in live settings.

Snowflake Snowpark Integration:

• Collaborate with data engineering teams to leverage Snowflake Snowpark for building and deploying data-intensive AI models.
• Implement data pipelines and machine learning workflows within Snowflake, optimizing the integration of large-scale data with AI models for enhanced performance and insights.

Collaborate with Cross-Functional Teams:

• Work closely with product managers, data scientists, and engineers to identify key areas where AI can drive significant business value.
• Translate complex AI concepts into actionable solutions that align with organizational goals.

Continuously Improve AI Solutions:

• Stay up-to-date with the latest advancements in AI technology, including new techniques in deep learning, natural language processing, and computer vision.
• Implement improvements to existing AI solutions based on performance monitoring and feedback from stakeholders.

Mentor and Guide Junior AI Engineers:

• Provide technical mentorship to junior team members, fostering a culture of learning and innovation within the AI engineering team.
• Participate in code reviews and ensure adherence to high-quality coding standards and best practices.

Ensure Data Privacy and Security:

• Adhere to best practices in data privacy and security when working with sensitive data, ensuring all AI solutions comply with relevant regulations.

Requirements/ Experience:

• Minimum of 4 years of professional experience in AI engineering or related roles.
• Extensive experience in fine-tuning and customizing LLMs, particularly in the context of generative AI and text-based applications.
• Proven track record of developing and implementing RAG models, with a focus on optimizing vector databases and embedding strategies.
• Hands-on experience with Snowflake Snowpark, including building and deploying AI models within Snowflake’s data platform.
• Proficiency in using AI frameworks such as TensorFlow, PyTorch, LangChain, and tools like Azure AI Studio, Snowflake Cortex, and OpenAI.

Soft Skills:

• Strong analytical and problem-solving skills with a deep understanding of AI concepts, including deep learning, natural language processing, and reinforcement learning.
• Excellent communication skills, capable of articulating complex AI concepts to both technical and non-technical stakeholders.
• Ability to work independently and collaboratively in a fast-paced environment, managing multiple projects simultaneously.
• Detail-oriented and committed to delivering high-quality, scalable AI solutions.

Education:

• Bachelor’s or master’s degree in Computer Science, Data Science, or a related field is preferred.
• Relevant certifications in AI or related areas are a plus.