Machine Learning Engineer

About the role

Our Mission

Our mission is to build the performance layer for the blended workforce: one standard, one system, where every human and AI agent is evaluated, coached, and improved together.

Today, Intryc is the platform where fast-growing and enterprise companies evaluate and train their human and AI CX agents. Our customers automate ticket, call, chat, and email scoring, surface patterns and insights in minutes instead of weeks, and turn every finding into targeted training. We are trusted by multi-billion dollar companies and breakout startups including Deel, MaintainX, Preply, Blueground, Fyxer AI, and Ziina.

But quality assurance and training are the beachhead, not the destination. The customer service and experience tech landscape is broken: fragmented tools, siloed data, dashboards that describe problems without fixing them. We intend to replace it. Our ambition is that every customer conversation, whether handled by a person or a model, is measured, understood, and made better by Intryc. When AI is expected to do the work of the best humans, someone has to define what best means and hold everyone to it. That someone is us.

About us

Behind Intryc is a team of ex-Meta, Amazon, Revolut, Confluent, and Twitter operators who spent over seven years raising the bar for customer experience inside those companies. We lived the painfully manual, repetitive, error-prone reality of support QA firsthand. We built Intryc so CX teams can focus on what actually matters: their customers and their business goals.

We went through Y Combinator (S24), we are growing fast, and our US client base is growing fastest of all, which is why we are scaling our presence from our San Francisco HQ.

Our Culture

We do not hide behind fancy titles or bureaucratic processes. We treat people equally and fairly and give them full freedom and autonomy to create something awesome. We back everything with data and logic. We make mistakes, learn from them, and move on. It is all about getting stuff done and owning what you do.

We maintain an extremely high talent density and we do not lower the bar for anything or anyone. We look for smart, ambitious, paranoid people who care deeply about their work and about other human beings. What we offer in return is high agency, real ownership, and real risk and reward.

Our Values

- Fired up and Get Shit Done

- Customer obsessed

- Be open, transparent, and accountable

- Be smart, humble, and empathetic

- Be frugal

- Take action if the outcome is reversible

Responsibilities

- Collaborate with the team to design, implement, and fine-tune ML models, focusing on LLM-based systems.

- Develop and enhance Retrieval-Augmented Generation (RAG) pipelines for intelligent query processing and knowledge retrieval.

- Experiment with and evaluate pre-trained models and fine-tune them for specific tasks.