Senior Machine Learning Engineer - Algs

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June 28

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Keebo

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Artificial Intelligence • Enterprise • SaaS

Keebo is a company specializing in fully automated optimization solutions for Snowflake data warehouses. Known as "The Snowflake Savings Machine," Keebo uses its patented technology to automatically adjust settings like warehouse size, clustering, and memory to save customers significantly on their Snowflake costs. The platform is designed to be user-friendly and secure, using only telemetry metadata while offering full visibility and control over optimizations. Setup is simple, requiring only 30 minutes, and users can start realizing savings within 24 hours without impacting performance. Keebo's solution stands apart by delivering real-time cost optimizations and performance protection continuously, unlike other tools that only report data without taking proactive actions.

11 - 50 employees

🤖 Artificial Intelligence

🏢 Enterprise

☁️ SaaS

💰 Series A on 2022-10

📋 Description

• Research, implement, and tune cutting-edge RL/ML models to achieve critical business outcomes • Design and implement AI/ML models that balance quality, speed, and cost • Collaborate with the rest of the Algorithms team to achieve goals that drastically impact the revenue of the business • Build repeatable, reliable pathways for promoting ML models from development to production

🎯 Requirements

• Experience as a machine learning engineer, working on real-world problems impacting live customers • Experience developing ML models end to end and deploying into production environments • Experience building and maintaining scalable, reliable, and safe ML models that directly impact customers’ experience • Experience implementing AI/ML models that balance quality, speed, and cost • Experience automatically monitoring the quality and effectiveness of ML/AI models from local dev through to production • Experience with SQL, data analysis, and databases • Experience with Python, and strong track record of writing readable, maintainable production code • Experience with GCP or AWS • Skilled in being self-directed and moving quickly to build and improve systems and architectures • Ability to work in a fast-paced early stage startup • Skilled at communicating effectively in a distributed environment with people across multiple time zones • Strong self-motivation, initiative, and adaptability

🏖️ Benefits

• Competitive salary packages • Equity • Home office stipend • Comprehensive medical, dental, and vision benefits • 401k retirement program • Annual company offsite (this year the team met up in Cancún, Mexico!) • Paid time off • Paid parental leave