AI - ML Engineer

Responsibilities:

• Design, develop, and deploy LLM-based applications for AI-driven CRM solutions on Salesforce.
• Implement Retrieval-Augmented Generation (RAG) architectures to optimize the contextual accuracy of LLMs within the Salesforce environment.
• Leverage Vector Databases (e. g., Pinecone, FAISS, or Weaviate) to manage and retrieve high-dimensional data for AI applications.
• Integrate external knowledge sources into AI models, enhancing their ability to deliver contextual and business-relevant insights.
• Collaborate closely with cross-functional teams (including RevOps, data, and engineering) to ensure AI solutions align with business objectives and scale effectively.
• Stay up-to-date with advancements in AI, including LLMs, RAG architectures, and innovations in database and cloud technology.

Requirements:

• Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a related field.
• Proven experience working with LLMs (e. g., GPT, BERT) and implementing them in production-level applications.
• Expertise in RAG architecture for improving model relevance and performance in AI-driven systems.
• Strong experience with Vector Databases to handle large-scale, high-dimensional data.
• Proficiency in Python and ML frameworks (e. g., TensorFlow, PyTorch, Hugging Face).
• Familiarity with deploying AI/ML models on cloud platforms (e. g., AWS, Azure) with a focus on scalability.
• Excellent problem-solving skills and ability to work collaboratively in a dynamic, fast-paced environment.

Preferred Skills:

• Experience with MLOps for scaling and automating ML model deployment and management.
• Familiarity with graph databases and semantic search technologies.
• Understanding of AI-driven product development lifecycle, from data collection and model development to deployment and performance monitoring.
• Experience integrating AI models with CRM systems.

Skills

BERT, GPT, LLM, Python, RAG