AI/ML Engineer
Hybrid San Francisco Full-time Mid-level Machine Learning Engineering
At a glance
Mid-level Machine Learning Engineering role at Hop. San Francisco · full-time · no salary stated · we estimate $197,625–$279,000.
Estimated pay
Hop has not published a salary for this role. The figure below is our estimate, not theirs.
$197,625 – $279,000
What the middle half of mid-level machine learning engineering roles in San Francisco paid, among postings that did state a salary.
Worked out from 50 postings that stated pay, median $240,000. Last updated Oct 21, 2026.
RoleMachine Learning Engineering
SeniorityMid-level
LocationSan Francisco
WorkplaceHybrid
EmploymentFull-time
PostedApr 22, 2026 · 6mo ago
Role brief
aimlroles summary, based on the employer's posting.
What you'll do
- Build and support LLM workflows and agents that run in production
- Shape RAG systems around vector databases, tuning them for large-scale use
- Create agents that use tools, coordinate with other agents and run reasoning cycles
- Handle prompts, model releases, evaluations and operational tracking for LLMs
- Connect AI features to data pipelines and maintain production monitoring and safeguards
What you bring
- A computer science, machine learning or related degree at the bachelor's or master's level
- Three to five years in AI/ML engineering, including at least two years shipping LLM-based systems
- Strong Python skills plus experience with PyTorch or Hugging Face Transformers, cloud platforms and container tools
- A portfolio demonstrating shipped AI work, such as agent pipelines, retrieval systems or tuned models
Who this fits
This role suits a mid-level AI/ML engineer with hands-on experience delivering LLM systems. You’ll work from the San Francisco office at least four days each week. You must already have U.S. work authorization that does not require employer sponsorship now or later.
From the employer
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 — minimum 4 days per week in-office.
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.
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 — minimum 4 days per week in-office.
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.