Remote Lead AI/ML Engineer — End-to-End Production Systems

loom ai; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Direct access to founders

Equity on conversion

Equity opportunity

Job summary

loom ai seeks a results-driven ML engineer to own end-to-end production AI systems for real enterprise data. You will ingest signals in real time, build scoring models, and deploy safe, scalable frameworks with a human gate for critical changes.

You will work directly with founders and enterprise clients, applying RAG, prompt engineering, and model fine-tuning to drive measurable improvements and equity upon conversion. This is a remote role in the United States with growth potential.

Qualifications

• 3–5 years of ML engineering or applied AI — production systems, not notebooks.
• Python fluency; traditional ML and modern AI stacks.
• RAG, prompt engineering, evaluation harnesses, and/or fine‑tuning on domain‑specific data.
• Agent orchestration — systems where models make, route, or compose decisions.
• Full model lifecycle: training, evaluation, shadow, canary, A/B, ongoing tuning.
• Client presence — explain a model to a CFO.

Responsibilities

• Own end-to-end ML platform including data pipelines, models, and deployment frameworks.
• Ingest and structure signals from enterprise data sources in real time.
• Use LLMs to detect patterns and propose retraining needs.
• Collaborate with enterprise clients and domain experts.

Skills

Python fluency

Production ML systems

Prompt engineering

Evaluation harnesses

Domain data understanding

Client-facing communication

Startup mindset

Tools

LightGBM

XGBoost

scikit-learn

LangChain

LlamaIndex

OpenAI API

Anthropic API

Job description

loom ai seeks a results-driven ML engineer to own end-to-end production AI systems for real enterprise data. You will ingest signals in real time, build scoring models, and deploy safe, scalable frameworks with a human gate for critical changes.

You will work directly with founders and enterprise clients, applying RAG, prompt engineering, and model fine-tuning to drive measurable improvements and equity upon conversion. This is a remote role in the United States with growth potential.