Engineering Manager, Applied AI

October 2

🏄 California – Remote

Although this job is listed in California, this company may be open to hiring remote in other states.

⛰️ Colorado – Remote

Although this job is listed in Colorado, this company may be open to hiring remote in other states.

+1 more states

🏄 California – Remote ⛰️ Colorado – Remote 🍂 Massachusetts – Remote

💵 $200k - $250k / year

⏰ Full Time

🟠 Senior

🔴 Lead

👮‍♀️ Software Engineering Manager

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Compa

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Technology • Life Sciences • Retail

Compa is a technology company specializing in real-time compensation data solutions for various industries, including life sciences, technology, and retail. They provide AI-driven insights and benchmarking tools that help organizations make informed compensation decisions based on up-to-date market trends. Compa connects seamlessly with client systems, ensuring their compensation data is always current and accurate, thus improving hiring and pay practices across diverse sectors.

51 - 200 employees

Founded 2020

🛒 Retail

📋 Description

• Build and lead Compa’s first Applied AI Team • Own and shape how we apply machine learning across both customer-facing products and internal systems • Operate as a player-coach—contributing hands-on to ML projects while building a high-performing team from the ground up • Work closely with Compa’s Co-founder & CTO to define the team’s technical vision, processes, and success metrics • Collaborate cross-functionally with Product, Engineering, CS, and Design to identify high-impact opportunities and ship production-grade ML systems that support comp decisions • Responsible for end-to-end ownership of applied AI initiatives, including model development, MLOps, roadmap planning, infrastructure alignment, and organizational process design

🎯 Requirements

• 7+ years of experience as a technical lead or manager on ML or Applied AI teams • Proven experience shipping production ML models in customer-facing or business-critical applications • Strong engineering fundamentals and a “builder” mindset—you’re comfortable rolling up your sleeves to write or review code • Familiarity with modern ML tooling, MLOps practices, and model evaluation pipelines • Experience collaborating with Product Managers and cross-functional stakeholders to translate ambiguous problems into technical strategies • Strong communication and leadership skills, with experience aligning teams and driving delivery • Ability to create and scale process, tooling, and team practices in a fast-paced, early-stage environment

🏖️ Benefits

• Offers Equity