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 reliability.
Role type
Machine Learning Engineer (LLMs & Agentic Systems)
Builds
Production-ready conversational and autonomous agents, LLM features, and evaluation pipelines for a B2B sales intelligence platform.
Domain
AI for Sales / B2B SaaS
Deliverable
production ML models
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), MCP (Model Context Protocol), ASR systems
Technologies
Python, LangChain, LangGraph, FastAPI, Uvicorn, DeepEval, MCP, ASR
Responsibilities
Design and optimize the agentic stack for reliability and low latency; Architect and maintain end-to-end LLM features including orchestration and monitoring; Develop ML infrastructure for observability and scaling; Build robust evaluation datasets and pipelines for deterministic and non-deterministic systems; Collaborate with software engineers on scalable infrastructure; Work with product managers to refine specs and deliver features; Contribute to technical strategy and roadmap; Stay updated on LLM research and open-source methodologies.
