Hybrid Staff AI Engineer

at Laurel

• Job title: Staff AI Engineer
• Job type: Full Time
• Experience level: Lead
• Salary: $200,000 - $250,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Airflow, AWS, Azure, Cloud, Docker, Python, PyTorch, SQL, Tensorflow
• Location requirements: Hybrid, San Francisco, United States

About the role

• AI Engineer shaping AI solutions for Laurel's AI Time platform. Collaborating across the stack from data pipelines to production-grade features.

Responsibilities

• Own business‑critical AI challenges. Partner with product, design, and engineers to uncover the real customer problems, then frame them as tractable machine‑learning tasks
• Build end‑to‑end solutions, collect and curate data, prototype models, run rigorous experiments, and productionize the winners with reliable MLOps practices and your code will move effortlessly between exploratory notebooks and hardened services
• Ship incrementally, learn rapidly, break ambitious ideas into testable slices, measure impact, and iterate
• Elevate the team and mentor engineers on best practices in ML engineering, model evaluation, prompt design, and responsible AI
• Introduce tools and techniques that improve reliability, speed of deployment, fairness, and performance
• Take true ownership and empower every team member to understand the business levers behind their work and to push for outcomes, not just tickets
• Aid in building out Laurel's AI platform to support billions of inferences

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• 5+ years of professional experience in building production machine learning solutions, with a focus on NLP, language models, and embeddings
• Strong proficiency in Python
• Comfort with at least one deep-learning framework such as PyTorch or TensorFlow
• Hands-on experience building text-processing pipelines
• Solid grasp of LLM evaluation metrics (BLEU, ROUGE, BERTScore, human preference scoring)
• Strong SQL skills
• Experience with cloud platforms (AWS and Azure)
• Demonstrated MLOps experience
• Orchestration and pipeline (Airflow)
• Experiment tracking (MLFlow)
• Containerization with Docker

Benefits

• Great employee benefits, including equity and 401K
• Bi-annual, in-person company off-sites, in unique locations, to grow and share time with the team
• An opportunity to perform at your best while growing, making a meaningful impact on the company's trajectory