RL Environments Engineer - Build AI Training Pipelines

SimpleClosure; New York (NY); Hybrid; USD 140,000 - 200,000; Full time

Benefits offered by this job

Competitive equity

Health benefits

Life insurance

Unlimited PTO

Hybrid work in NYC Midtown

Offsites twice a year

401(k) retirement plan

Job summary

SimpleClosure is seeking an AI/ML Engineer to transform Asset Hub’s real assets into high-value AI-training products such as RL environments, task suites, and evaluators. You’ll prototype fast, then turn ideas into scalable pipelines, working with a small Asset Hub pod alongside product, engineering, and leadership.

Candidate must have hands-on experience building environments for training/evaluation, with 4–8 years in ML/AI engineering, strong Python and Docker skills, and a growth mindset for

Qualifications

• RL-environments or AI-training background with deployed assets.
• 4–8 years of engineering experience in RL/environments or model evaluation.
• Strong Python, containers (Docker), and CI/test infra.
• Familiarity with LLM evaluation and verifier/reward design basics.
• Ownership mindset and ability to drive projects end-to-end.
• Clear communication with labs and RLE researchers.
• Nice-to-have contributions to benchmarks or eval frameworks.
• Bachelor’s or Master’s in CS/ML, or related practical experience.

Responsibilities

• Turn Asset Hub assets into high-value AI-training products: RL environments, task suites, evals, and datasets.
• Design and build the pipeline to derive products from raw assets: ingestion, test harnessing, commit-mining, reproducibility, verifier scripts, QA tooling.
• Wrap data in interactive environments with sandboxed state, MCP servers, and Playwright layers for training/evaluation.
• Spot commercial opportunities mapping assets to lab RLE demand for max value.
• Prototype quickly and harden into repeatable, scalable pipelines.
• Partner with asset buyers/BD and with labs to shape training needs.
• Handle sensitive material with attention to security, privacy, licensing, and PII.
• Write clean, well-tested code and collaborate with product, engineering, and GM of Asset Hub.

Skills

RL environments

AI training data

Python

Docker

CI / testing

Evaluator design

Ownership

Communication

Public benchmarks

Post-training data

Playwright

Education

BS/MS in CS/ML

Tools

Docker

Playwright

MCP servers

Job description

SimpleClosure is seeking an AI/ML Engineer to transform Asset Hub’s real assets into high-value AI-training products such as RL environments, task suites, and evaluators. You’ll prototype fast, then turn ideas into scalable pipelines, working with a small Asset Hub pod alongside product, engineering, and leadership.

Candidate must have hands-on experience building environments for training/evaluation, with 4–8 years in ML/AI engineering, strong Python and Docker skills, and a growth mindset for