🚀 About Compa

Compa is a venture-backed SaaS startup revolutionizing the future of compensation.

In a dynamic job market with hiring challenges, accountability, and the rise of AI, companies need the best data to stay ahead of industry changes, competition, and costs. Compa has developed the premier real-time compensation data platform, delivering top-tier compensation intelligence to leading enterprise teams.

Compa is a compensation intelligence company built to augment enterprise compensation teams in the era of AI.

Our customers include the world’s biggest companies: NVIDIA, Stripe, DoorDash, TMobile, Moderna, Workday, Ulta, Target, and more.

Locations:

Compa headquarters are located in Irvine, California, with growing sites in Denver, Colorado and San Francisco, California. We’re a collaborative, curious, and driven team that values transparency, ownership, and continuous learning and prioritizing in person work where possible.

The Role:

As an Applied AI Engineer on the Engineering team at Compa, you will own and lead projects across Compa’s product suite, internal operations, and be part of a team that takes a commercialized prediction service from 0 to 1.

In this role you will:

• Ship ML features that enable the world’s best companies to make smarter pay decisions

• Lead ML-based projects from end-to-end: scoping and planning, data collection and feature engineering, model training and deployment, backend implementation, and online experimentation

• Prototype machine learning features for use in product and work with product teams and customers to iterate on requirements

• Develop, productionize, and operate machine learning models for use in Compa’s product suite, internal operations, and a commercialized prediction service

• Drive technical excellence and establish ML best practices across the team

Minimum Qualifications:

• 4+ years of industry experience building and deploying ML models to solve user problems

• Industry experience with a track record of applying practical methods to solve real-world problems

• Experience in applied statistical and machine learning fields e.g. classification, recommendations, content understanding, natural language processing, and large language models, etc.

• Proficiency in Python, SQL, and common ML frameworks.

• Gumption — experience working at early-stage startups

Preferred Qualifications:

• Experience with data pipeline technologies

• Experience with cloud platforms (AWS, GCP, Azure, etc.)

• Exposure to agentic systems, predictive modeling, or real-time data products