AI/ML Engineer
👨💼 Roles: AI/ML Engineer
👨💼 Experiences: Experienced Required
🏢 Companies: Exact Solution Electronics
🗓 Posted: 2026-08-31
⏳ Expires: 2026-09-14
🚀 We’re Hiring: AI/ML Engineer | Exact Solution Electronics
📌 Employment Type: Full-Time
🌍 Location: Remote
Exact Solutions is looking for an experienced AI/ML Engineer to build and productionize intelligent grading and recommendation systems for device diagnostics, cosmetic condition, repair routing, and resale outcomes.
🔹 What You’ll Do
Design and train grading models that recommend A–F grades using structured diagnostic results, cosmetic evidence, and device specifications.
Build confidence scoring and explanation outputs for every AI recommendation, including grade, repair, route, and price.
Develop an image-based cosmetic grading pipeline to identify screen cracks, body damage, camera lens condition, and other defects.
Implement an outcome learning loop connecting grade/repair decisions to actual resale price, days-to-sell, and return events to continuously improve model accuracy.
Integrate AI recommendations into our Django platform API as non-blocking, auditable suggestions.
Enforce clear AI authority boundaries: AI recommends only—it cannot alter observed hardware evidence, declare sanitization successful, or clear a lock state.
Build and maintain model governance, including versioning, confidence thresholds, drift detection, and override tracking.
Collaborate with the QA team to define AI quality gates before every release.
🔹 Qualifications
3+ years of experience in applied ML/AI, with production models—not just notebooks.
Strong experience with structured/tabular data models, such as XGBoost, LightGBM, or similar.
Experience with computer vision, including image classification and defect detection, is a strong plus.
Familiarity with MLOps, model versioning, monitoring, and retraining pipelines.
Strong Python proficiency and experience integrating ML models into REST APIs; Django/FastAPI preferred.
Understanding of explainability techniques, such as SHAP, LIME, or confidence intervals.
Experience working with small, noisy, real-world datasets, rather than only clean benchmark datasets.
📩 Interested? Apply now.
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