Flatworld Solutions - Senior AI Model Testing & Validation Engineer

Job Description : We are seeking an AI Model Testing & Validation Engineer with deep expertise in validating AI/ML models and extensive experience with Bluetooth-enabled connected systems. This role requires technical leadership in defining validation strategies for AI models deployed on edge and embedded devices, ensuring performance, reliability, safety, and scalability under real-world connectivity constraints.Key Responsibilities : Core Competencies & Skills : - Expert in AI/ML model testing and validation across the full lifecycle, from experimentation to production deployment.- Advanced experience validating ML, Deep Learning, and Edge AI models for accuracy, robustness, generalization, and drift.- Strong expertise in model evaluation metrics, statistical validation, cross-validation, and error analysis.- Proven ability to design automated AI validation frameworks and reusable test harnesses in Python.- Deep understanding of bias, fairness, explainability, and AI safety validation (SHAP, LIME, interpretability techniques).Bluetooth & Connectivity Expertise : - Extensive hands-on experience with Bluetooth Classic and Bluetooth Low Energy (BLE).- Strong knowledge of Bluetooth protocols, profiles, pairing, security, power management, and coexistence.- Expertise in validating AI model performance under real-world Bluetooth conditions (latency, jitter, packet loss, interference, reconnections).- Experience with interoperability testing across chipsets, stacks, OS versions, and devices.- Skilled in protocol-level debugging and connectivity performance analysis.Edge AI & Embedded Systems : - Experience validating on-device AI inference on constrained systems (MCUs, DSPs, NPUs).- Expertise in testing quantized, compressed, and optimized models for latency, power, and memory efficiency.- System-level understanding of AI integration with firmware, drivers, and connectivity stacks.- Familiarity with RTOS, embedded Linux, and edge accelerators.MLOps, Quality & Governance : - Strong experience with MLOps pipelines, CI/CD, model versioning, monitoring, and drift detection.- Ability to define validation standards, acceptance criteria, and go/no-go metrics.- Experience producing validation documentation for audits, certifications, and compliance reviews.- Knowledge of Responsible AI and model risk management practices.Nice to Have : - Experience in medical devices, wearables, or IoT ecosystems.- Knowledge of AI safety, Responsible AI, or model risk management frameworks.- Experience validating multimodal or sensor-fusion models.- Familiarity with edge accelerators and real-time operating systems (RTOS).- Technical leadership in defining AI validation strategy and best practices.- Strong cross-functional collaboration with firmware, product, and QA teams.Education & Experience : - Bachelors or Masters degree in Computer Science, Electrical Engineering, AI, or related field.- 6-8 years of experience in AI/ML, embedded systems, or connectivity testing. (ref:hirist.tech)