AI//ML Engineer (NLP & Computer Vision)

Position Overview

This company is hiring a full-time ML // AI Engineer to work on-site in Location: San Francisco. Schedule: Full-time. In this role, you will build production machine learning systems for large enterprise customers at the intersection of applied ML, NLP, LLMs, and real-world systems engineering. You’ll design and ship models that turn noisy enterprise data into measurable insights with an emphasis on accuracy, latency, and cost. Applicants must be currently authorized to work in the US on a full-time basis now and in the future.

Key Responsibilities

• Design, implement, and ship production machine learning systems that process unstructured signals such as OCR output, application metadata, and behavioral telemetry at scale.
• Operate at the intersection of applied ML, NLP, and LLM orchestration, ensuring solutions are both innovative and efficient.
• Collaborate with founders, customers, and team members to take ownership of zero-to-one projects.
• Balance hands-on development with strategic team collaboration as indicated by a 50% split in daily responsibilities.

Required Qualifications

• Strong Python skills and solid software engineering fundamentals.
• Hands-on experience building classification and NLP systems.
• Expertise in prompt design and optimization for LLMs, including few-shot strategies, token efficiency, and reasoning scaffolding.
• Experience designing evaluation frameworks with ground truth creation, A/B testing, and accuracy analysis.
• Production ML experience covering deployment, monitoring, and performance tuning.
• Ability to navigate ambiguity and tackle unexplored technical challenges.

Preferred Qualifications

• Experience with hybrid ML and rule-based architectures.
• Background in OCR, document intelligence, or computer vision.
• Proven strategies for cost control in LLM-centric systems.
• Experience with PyTorch or similar frameworks.
• Familiarity with process mining or workflow analytics.
• A track record of shipping ML systems that operate at scale under real constraints.
• Personal projects demonstrating technical depth and curiosity.

Benefits & Perks

• Benefits: Medical, Dental, and Vision Insurance.
• Vacation Time.
• Equity.