# Machine Learning Engineer - Conversational AI

**Company**: Spotify
**Location**: New York
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $184,050-$262,928
**Category**: Engineering
**Industry**: Technology

**Apply**: https://jobs.lever.co/spotify/b2123f20-234d-439d-8048-0fac5afa4564
**Canonical**: https://yubhub.co/jobs/job_90dd92c2-5da

## Description

The Personalization team at Spotify makes deciding what to listen to next feel effortless for hundreds of millions of users , from Discover Weekly to our newest AI-powered experiences. We're now building conversational AI capabilities that let users interact with Spotify in natural language. You'll join a squad working at the core of this space, shaping how users discover and engage with audio through intelligent, responsive systems.

### Responsibilities

- Design and ship production-grade machine learning systems powering conversational and agentic AI experiences

- Build systems that interpret user intent, manage context across multi-turn interactions, and handle ambiguity reliably at scale

- Develop and evolve agentic workflows including memory, context management, and multi-step tool orchestration

- Create evaluation frameworks, including LLM-as-judge pipelines, to measure quality and guide iteration

- Partner closely with product, engineering, and design to deliver seamless, user-facing experiences

- Balance experimentation with production rigor, ensuring performance, latency, and reliability at Spotify scale

- Continuously improve agent behavior through tight feedback loops between evaluation and real-world usage

### Requirements

- 5+ years of experience building and shipping machine learning systems in production environments

- Experienced with large language models and have worked on real-world applications beyond experimentation; shipped and maintained large scale systems with LLMs

- Deep understanding of challenges in conversational or agentic systems, such as context handling and multi-step reasoning

- Know how to evaluate ML systems rigorously and have experience designing metrics or evaluation pipelines

- Comfortable debugging complex interactions between models, tools, and system constraints like latency

- Care about building reliable, scalable systems that deliver high-quality user experiences

- Enjoy working cross-functionally and contributing to a collaborative, inclusive team environment

## Skills

### Required
- machine learning
- conversational AI
- natural language processing
- large language models
- agentic workflows