Machine Learning Engineer

🚀Role: ML Engineer Job Type: Contract/Fulltime Location: Remote 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 5,000 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 What You Do Not Need • Experience in fashion or apparel — consumer behavior data is consumer behavior data; retail, CPG, or e-commerce forecasting experience is equally relevant • Deep SAP or ERP integration experience — the pilot will use manual file transfers where needed; backend integration is Phase 2 • A large team or large compute budget — the pilot is lean by design; the models need to work with limited data and limited infrastructure Nice to Have • Experience with social commerce data pipelines — TikTok and Instagram engagement signals as demand proxies • Familiarity with micro-batch production economics — unit economics of 50–500 unit test runs versus full production scaling • Experience building consumer persona or segmentation models using LLMs. 📩 Share your resume at: nidhi.singh@nlbtech.com