Intryc uses AI to automate quality assurance for customer support. Consumer enterprises have millions of customer support tickets annually. They need to constantly evaluate support agents’ performance and compliance. Typically they evaluate 4-5% of those interactions manually but it's slow, expensive and not scalable. Intryc's AI can evaluate 100% of all customer interactions, in real time, at half the cost.

About us

Behind Intryc is a squad of ex-Meta, Amazon, Revolut, Confluent, and Twitter folks who spent over 7 years leveling up customer experience for these companies. We know first hand how painfully manual, repetitive, and error-prone Support QA processes are. That’s why we built Intryc, to solve this so that customer support teams can focus on what really matters to them – their customers and business goals.

Our passion that fuels our mission at Intryc comes from our conviction that we are at an inflection point, fuelled by the rapid evolution and proliferation of GenAI and LLMs, that will fundamentally change how humans interact with the digital realm. Even though LLMs are still nascent in their adoption and far from perfect in their everyday use, we believe that we’re experiencing a turning point similar to the dawn of the internet in our every day lives. Human-LLM interactions are rapidly evolving and have the potential to provide tenfold improvements in how things are done today across various industries and functions.

Our Culture

At Intryc, we don’t hide behind fancy job titles or set up bureaucratic processes. Instead, we treat our people equally and fairly and give them full freedom and autonomy to create something awesome. We care deeply about our customers and strive to create something big that will add value to the world in each interaction. We make mistakes, we learn from them, move on, and we back everything up with data and logic. It’s all about getting stuff done and owning what we do. We’re bringing onboard exceptional talent to help us build the world’s leading Support Quality Management and Insights AI co-pilot.

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.
• Work with large-scale datasets to ensure efficient indexing, retrieval, and contextual relevance.
• Monitor and improve the performance and scalability of deployed models.
• Stay updated with the latest research in LLMs, RAG, and related fields.
• Assist in debugging, testing, and deploying machine learning pipelines.
• Gather customer feedback and iterate on the models' accuracy based on customer use cases.

Qualifications

Required Skills:

• Bachelor's degree in Computer Science, Data Science, or a related field.
• Foundational knowledge of machine learning algorithms and model development.
• Understanding of LLMs (e.g., OpenAI GPT, Hugging Face models) and their applications.
• Basic knowledge of retrieval systems (e.g., Elasticsearch, FAISS, or vector databases).
• Familiarity with the RAG paradigm or similar architectures for context-aware systems.
• Proficiency in Python and common ML libraries.
• Strong problem-solving skills and a passion for learning new technologies.

Preferred Skills:

• Experience fine-tuning LLMs for domain-specific applications.
• Exposure to NLP tasks like summarization, translation, and Q&A systems.
• Knowledge of cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).

Benefits

• You’ll get to work with incredible talent in a hot and fast-growing start-up in the Gen AI and LLM space.
• Generous stock options.
• Competitive salary.
• Remote first policy with 25 days of holiday a year plus bank holidays.
• Pension plan.
• Private health insurance.
• We’ll arm you with all of the latest tech equipment.

On a high level, our tech stack is react/remix and python. We are in AWS. We are currently adding LLMs and other novel ML algorithms to our infrastructure to perform operational and analytics tasks. We will have to fine tune, train, and improve to ensure accuracy, while keeping our customers data secure. The core focus is to build the application and scale it to multiple clients and high volumes of data. We are currently onboarding large enterprise clients and we are expecting critical and high data/events volume.