Applied AI/ML Engineer

📋 Description

• LLM systems and prompt architecture: design prompts, outputs, and orchestration.
• Evaluation frameworks: build scalable AI-quality eval infra with tools.
• Model experimentation: run structured experiments for quality, cost, latency.
• AI observability and tooling: dashboards, debugging workflows.
• Matching and ML systems: improve match quality with lightweight models.
• Model serving and production inference: deploy, versioning, cost/latency optimization.

🎯 Requirements

• 5+ years of engineering experience building LLM-powered products.
• Strong prompt engineering and evaluation instincts.
• Experience building evaluation pipelines for LLM systems.
• Familiarity with vector databases and retrieval-augmented architectures.
• Experience with fine-tuning techniques such as SFT, DPO, RLHF.
• Experience with Python, SQLAlchemy, FastAPI, PostgreSQL.

🎁 Benefits

• Stock options with upside potential.
• Health and dental insurance.
• In-person work in NYC office.