ML Engineer
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Job Location:
Costa Mesa, CA - USA
Monthly Salary:
Not Disclosed
Posted on:
4 hours ago
Vacancies:
1 Vacancy
Job Summary
ML Engineer
Location: Remote with periodic travel to Costa Mesa CA
Location: Remote with periodic travel to Costa Mesa CA
Client is building an AI-native product creation pipeline for a global apparel and footwear company - a 90-day sprint to design manufacture and place real products on retail shelves without using the traditional 18-month fashion calendar. The proof of concept is simple: 5000 units one category 90% full-price sell-through.
The ML Engineer owns the intelligence layer that makes this possible. You will build the models that tell the team what consumers want before they know it themselves - and the forecasting logic that determines exactly how many units to produce in which sizes for which markets. Get this right and the pilot sells through cleanly. Get it wrong and the warehouse fills up with unsold backpacks.
What You Will Do
Build or configure consumer insights models that synthesize real-time social media signals search trends and behavioral data into actionable design briefs - replacing the 9-month $200K research agency process with near-real-time intelligence
Develop demand forecasting models at the SKU size and geography level to inform micro-batch production decisions - starting with 5000 units for the pilot and designed to scale
Integrate data inputs from social platforms (TikTok Instagram Google Trends) and commercial trend tools (Heuritech WGSN Stylumia) into a unified signal layer
Work with the AI Product Manager to define the data architecture for the pilot - lightweight enough to move fast in Phase 1 structured enough to scale in Phase 2
Validate model outputs against real sell-through data as the pilot progresses and iterate accordingly
Document model logic and data pipelines so the approach is repeatable across categories and brands
Build or configure consumer insights models that synthesize real-time social media signals search trends and behavioral data into actionable design briefs - replacing the 9-month $200K research agency process with near-real-time intelligence
Develop demand forecasting models at the SKU size and geography level to inform micro-batch production decisions - starting with 5000 units for the pilot and designed to scale
Integrate data inputs from social platforms (TikTok Instagram Google Trends) and commercial trend tools (Heuritech WGSN Stylumia) into a unified signal layer
Work with the AI Product Manager to define the data architecture for the pilot - lightweight enough to move fast in Phase 1 structured enough to scale in Phase 2
Validate model outputs against real sell-through data as the pilot progresses and iterate accordingly
Document model logic and data pipelines so the approach is repeatable across categories and brands
What You Need
Production-level experience building demand forecasting or consumer demand sensing models - time-series forecasting regression or ML-based approaches; you have shipped models that drove real inventory or production decisions
Hands-on experience with retail or consumer data - SKU-level sales data social listening data search trend data or equivalent; you understand how noisy and inconsistent this data is and how to work with it anyway
Familiarity with at least one commercial forecasting or trend intelligence platform - o9 Solutions Blue Yonder Heuritech Stylumia or equivalent
Strong Python skills and comfort working in cloud environments - models need to run in production and produce outputs the team can act on
Ability to communicate model outputs in plain language to non-technical team members - the tiger team includes a designer and a marketing lead; you need to translate forecast confidence intervals into decisions they can make
Production-level experience building demand forecasting or consumer demand sensing models - time-series forecasting regression or ML-based approaches; you have shipped models that drove real inventory or production decisions
Hands-on experience with retail or consumer data - SKU-level sales data social listening data search trend data or equivalent; you understand how noisy and inconsistent this data is and how to work with it anyway
Familiarity with at least one commercial forecasting or trend intelligence platform - o9 Solutions Blue Yonder Heuritech Stylumia or equivalent
Strong Python skills and comfort working in cloud environments - models need to run in production and produce outputs the team can act on
Ability to communicate model outputs in plain language to non-technical team members - the tiger team includes a designer and a marketing lead; you need to translate forecast confidence intervals into decisions they can make
Key Skills
- ASP.NET
- Health Education
- Fashion Designing
- Fiber
- Investigation
