Machine Learning Engineer
Core
Building and scaling LLM and agentic features for an AI platform dedicated to B2B sales, focusing on orchestration, tool execution, and production reliability.
Role type
Machine Learning Engineer (LLM & Agentic Systems)
Builds
Autonomous conversational agents, LLM features, and the underlying ML infrastructure for a B2B sales intelligence platform.
Domain
AI for Sales / B2B SaaS
Deliverable
production ML models | product features | infrastructure
Required skills
Python, LLMs (prompt design, evaluation, cost/performance trade-offs), agentic systems (tool execution, workflows, memory architectures), LangChain/LangGraph, NLP concepts (transcription, embeddings), ML fundamentals, FastAPI, Uvicorn, DeepEval, MCP
Preferred skills
Low-level languages (Java, C), ASR systems experience, open-source research in agentic systems
Technologies
LangChain, LangGraph, FastAPI, Uvicorn, DeepEval, MCP, Python
Responsibilities
Design and optimize the agentic stack for conversational agents; architect end-to-end LLM features including orchestration and monitoring; develop ML infrastructure for observability and scaling; build robust evaluation datasets and pipelines; collaborate with software engineers on scalable infrastructure; partner with product managers on feature feasibility and delivery; contribute to technical strategy and architecture decisions; stay updated on LLM and agentic system research.
Seniority
Mid-level (2-5 years experience), hands-on IC