ML Engineer – AI-Native Systems, Forecasting

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Ando

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2023

🤖 Artificial Intelligence

👥 HR Tech

☁️ SaaS

Artificial Intelligence • HR Tech • SaaS

Ando is an AI-native workforce intelligence platform that provides fine-grained demand forecasting and autonomous, optimized scheduling for hourly frontline operations. The SaaS product combines 15-minute interval predictive demand, an intelligent scheduling engine, a persistent labor data layer (availability, skills, reliability), verified worker identities (Ando Passport), recruiting triggers, and payroll/compliance integrations to reduce manual scheduling, improve manager efficiency, and align staffing to real demand across industries like restaurants, retail, logistics, and healthcare.

📋 Description

• You will own the design, development, and production deployment of Ando’s machine learning systems, including demand forecasting, labor allocation intelligence, and LLM-powered workflows. • This is a production ML role. You will work across the full data and ML lifecycle - from ingesting inconsistent real-world data to building reliable, continuously improving systems in production. • You will operate with high autonomy, make pragmatic modeling decisions, and build systems that directly impact real-world outcomes for businesses and workers. • This role is designed as a foundational technical leadership position, with meaningful influence over data architecture, model strategy, and system reliability. • Collaborate closely with Product, Engineering, and Operations to integrate ML into core workflows.

🎯 Requirements

• 5–10+ years of experience in machine learning, data science, or applied AI roles • Proven experience shipping ML systems into production environments • Strong experience working with real-world, imperfect datasets in mid-maturity or scaling organizations • Deep understanding of the full data stack, including ingestion, warehousing, feature engineering, and model serving • Experience designing and operating ML pipelines and workflows in production • Hands-on experience with LLM systems, including RAG, prompt design, and evaluation frameworks • Strong foundation in statistics, experimentation, and model evaluation • Experience with monitoring, observability, and model performance tracking over time • Ability to operate with high ownership, ambiguity, and minimal process overhead • Strong communication skills, with the ability to translate technical decisions into business impact.

🏖️ Benefits

• Health insurance • Remote work options