AI/ML Engineer

HopHR; San Francisco (CA); Hybrid; USD 120,000 - 160,000; Full time

Job summary

HopHR is building its Silicon Valley engineering team in San Francisco and seeks a skilled AI/ML Engineer. This role focuses on developing production-grade AI systems and involves significant responsibilities in building LLM pipelines and optimizing RAG architectures. The ideal candidate should have a BS/MS in Computer Science and 3–5 years of relevant experience, with strong skills in Python and tools like PyTorch, Docker, and AWS/GCP. This position offers a hybrid work arrangement, requiring a minimum of three days in the office each week.

Qualifications

• 3–5 years of AI/ML engineering experience.
• Minimum 2 years building LLM-powered systems in production.
• Portfolio of shipped AI work required.

Responsibilities

• Build and maintain production-grade LLM pipelines.
• Design RAG architectures using vector databases at scale.
• Integrate AI features into large-scale data pipelines.

Skills

AI/ML engineering

Python

PyTorch

Hugging Face Transformers

Docker

Kubernetes

Education

BS/MS in Computer Science or related field

Tools

AWS

GCP

Pinecone

FAISS

Weaviate

Job description

Draup is a Series A-funded agentic AI company building the intelligence layer for how global enterprises make workforce and go-to-market decisions. We work with 250+ enterprise clients — including 5 of the Fortune 10 — processing 1B+ job descriptions, 850M+ professional profiles, and signals from 100+ labor databases.

We are now building our Silicon Valley engineering team — a small, senior group focused on next-generation AI research and product.

Location: San Francisco, SoMa — Hybrid: minimum 3 days in-office per week, 2 days flexible.

What you'll do

• Build and maintain production-grade LLM pipelines and agentic workflows.
• Design and optimize RAG architectures using vector databases (Pinecone, FAISS, Weaviate) at scale.
• Implement agentic systems using LangGraph, LlamaIndex, or equivalent: tool use, multi-agent coordination, and reasoning loops.
• Own prompt engineering, model versioning, evaluation (RAGAS, DeepEval), and LLMOps instrumentation.
• Integrate AI features into large-scale data pipelines; maintain observability and guardrails in production.

What we require

• BS/MS in Computer Science, Machine Learning, or related field.
• 3–5 years of AI/ML engineering; minimum 2 years building LLM-powered systems shipped to production.
• Strong Python; PyTorch or Hugging Face Transformers; AWS or GCP; Docker/Kubernetes.
• Portfolio of shipped AI work required — agentic pipelines, RAG systems, or fine-tuned models.
• No visa sponsorship. Must be authorized to work in the US without current or future employer sponsorship.