ML Ops Engineer

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November 19

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Stord

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SaaS • Transport • eCommerce

Stord is a cloud supply-chain company that combines fulfillment network operations with integrated SaaS (OMS/WMS) to power omnichannel and DTC e-commerce brands. It provides warehousing, last-mile and transportation services, order routing, inventory management, and consumer-facing delivery tools to improve conversion, speed up fulfillment, and protect brand experience. Stord serves growing B2B and direct-to-consumer brands across food & beverage, beauty, apparel and other retail categories, offering a customizable fulfillment network and software platform to optimize costs and delivery performance.

1001 - 5000 employees

Founded 2015

☁️ SaaS

🚗 Transport

🛍️ eCommerce

📋 Description

• Take trained models from Data Scientist and deploy them to Modal.com or Vertex AI • Build APIs that serve model predictions with <100ms latency • Implement A/B testing frameworks for model comparison • Create model versioning and rollback strategies • Monitor model performance and catch drift before customers notice • Build real-time feature engineering pipelines using Kafka Streams or similar tooling • Create data validation and quality monitoring systems • Design feature stores that serve both training and inference • Implement efficient data transformations from our Postgres/AlloyDB sources • Ensure data consistency across ML and production systems • Develop CI/CD pipelines for model deployment • Build monitoring dashboards for model and pipeline health • Optimize inference costs across Modal, Cloudflare, and GCP • Create developer tools that make ML features easy to integrate • Document and evangelize MLOps best practices • Partner with the Data Scientist to understand model requirements • Work with platform engineers to integrate ML features into core Elixir services • Collaborate with product teams to define success metrics • Help other engineers understand and use ML capabilities

🎯 Requirements

• Strong Python (3+ years) • Strong TypeScript/JavaScript (2+ years) • MLOps Experience • Data Engineering • Cloud Platforms • Version Control • SQL Proficiency • Production Mindset • Pragmatic Approach • Strong Communication • Self-Directed • Learning Agility

🏖️ Benefits

• Flexible work arrangements • Professional development opportunities