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.

Experience
3-7 yrs