LLM/RAG Engineer — Remote, Stock Options, Growth

Socket.dev; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Remote-first policy

Generous stock options

Competitive salary

25 days holiday + bank holidays

Pension plan

Private health insurance

Latest tech equipment

Job summary

Intryc is seeking a talented ML Engineer to design, implement, and fine-tune ML models focused on LLM-based systems. You will develop RAG pipelines for intelligent query processing and knowledge retrieval, iterate on models with real customer use cases, and stay current with cutting-edge research in the field.

Remote-first with a US-focused client base, you will work on scalable ML solutions, indexing strategies, and deployment workflows to improve CX agent evaluation and coaching at scale.

Qualifications

• Bachelor's degree in CS, Data Science, or 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 (Elasticsearch, FAISS, or vector DBs).
• 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.

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.

Skills

Bachelor's degree

ML algorithms

LLMs

Retrieval systems

RAG paradigms

Python

Problem‑solving

Education

Bachelor's degree in CS/Data Science or related

Tools

Elasticsearch

FAISS

Vector databases

Docker

Kubernetes

Job description

Intryc is seeking a talented ML Engineer to design, implement, and fine-tune ML models focused on LLM-based systems. You will develop RAG pipelines for intelligent query processing and knowledge retrieval, iterate on models with real customer use cases, and stay current with cutting-edge research in the field.

Remote-first with a US-focused client base, you will work on scalable ML solutions, indexing strategies, and deployment workflows to improve CX agent evaluation and coaching at scale.