Machine Learning (ML)Responsibilities
● Design, build, and deploy applied ML models (NLP, LLM-based) to solve real-world sales tech problems.
● Build and orchestrate true multi-agent systems to collaboratively solve complex tasks and workflows that reason, remember, plan, and take actions over structured and unstructured data.
● Use frameworks like LangGraph, CrewAI, or custom planners to orchestrate LLM-powered agents.
● Prototype and productionize capabilities using foundation models (OpenAI, Claude, Gemini, etc.), embeddings, and vector databases (e.g., Pinecone, Weaviate).
● Work with the product team to integrate intelligent agents into customer CRM workflows and GTM-facing tools.
● Design observability, evaluation and control mechanisms to ensure agent reliability, traceability, safety and frugality.
● Continuously improve agents with RF and active learning.
Requirements
● Bachelor’s or Master’s in Computer Science, AI/ML, or a related field.
● 2+ years of experience deploying ML models or AI systems in production
environments.
● Experience with LLMs, NLP pipelines, prompt engineering, and fine-tuning.
● Familiarity with agentic frameworks (LangChain, LangGraph, AutoGPT, CrewAI, or custom orchestration).
● Strong Python programming skills and deep knowledge of the ML/LLM ecosystem.
● Hands-on experience with MLOps, API integrations, and cloud infrastructure (AWS, GCP, or Azure).
● Ability to balance rapid experimentation with robust engineering.
Nice to Have
● Experience working with sales/revenue data (CRM, Gong, Salesforce, LinkedIn).
● Familiarity with reasoning techniques (ReAct, CoT, Tree-of-Thoughts), graph orchestration, and tool chaining.
● Exposure to multi-agent systems, RAG pipelines, or feedback loops in production.
● Contributions to open-source AI/agentic tools or frameworks.
Shubham Vishwakarma
Full Stack Developer - Averlon
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Full Stack Developer - Averlon