**Hard Skills:**

- Deep Learning (TensorFlow, PyTorch)

- Edge ML Deployment (TensorFlow Lite, MLKit)

- IoT Protocols (MQTT, CoAP, OPC UA)

- Cloud Platforms (AWS IoT, Azure IoT Hub, Google Cloud IoT)

- Data Engineering & Streaming (Apache Kafka, Apache Spark)

- Sensor Data Processing & Analytics

- Model Optimization & Quantization for Edge Devices

- Python, C++, Java, SQL

**Soft Skills:**

- Problem-solving & Critical Thinking

- Cross-functional Collaboration

- Agile Development & Scrum

- Technical Documentation & Knowledge Sharing

- Adaptability in Emerging Tech Environments

*Senior Machine Learning Engineer | TechSense IoT Solutions*

San Francisco, CA | Jan 2023 – Present

- Led the development of an edge AI framework for a fleet of smart industrial sensors, reducing data transmission costs by 40% through onboard model inference.

- Architected a real-time anomaly detection system utilizing sensor fusion data streams, resulting in a 25% decrease in machine downtime.

- Collaborated with hardware teams to optimize ML models for low-power embedded devices, employing quantization and pruning techniques.

- Developed cloud-native pipelines on AWS IoT and Lambda functions for centralized model updates and alerts.

*IoT & ML Engineer | Innovatech Smart Devices*

Austin, TX | Aug 2019 – Dec 2022

- Designed predictive maintenance models for consumer home automation products, increasing customer satisfaction and reducing warranty claims by 15%.

- Implemented multi-modal sensor data handling combined with deep learning models, improving device activity classification accuracy by 12%.

- Managed end-to-end deployment of ML models on edge gateways, utilizing Docker containers and CI/CD workflows.

- Integrated MQTT-based messaging protocols with cloud analytics dashboards for real-time device monitoring.

Data Scientist | GreenGrid Energy Solutions

Remote | Jan 2017 – Jul 2019

- Developed energy consumption forecasting models using time-series analysis and LSTM networks to optimize grid load balancing.

- Built an IoT data lake on Azure Data Lake with automated ETL pipelines, yielding faster insights into power usage patterns.

- Conducted sensor data quality assessments, reducing data noise by 20% through preprocessing pipelines.

**Master of Science in Electrical Engineering**

University of California, Berkeley | 2014 – 2016

**Bachelor of Science in Computer Engineering**

Texas A&M University | 2010 – 2014

- Certified IoT Professional (CIoTP) – IoT Association, 2024

- TensorFlow Developer Certificate – Google, 2023

- AWS Certified Solutions Architect – Associate, 2022

Smart Agriculture IoT Platform

- Developed a machine learning-driven soil moisture and crop health monitoring system utilizing custom sensor arrays and edge devices.

- Deployed lightweight CNN models on Raspberry Pi-based gateways, enabling real-time insights to farmers via mobile app notifications.

Predictive Asset Monitoring System for Manufacturing

- Created a scalable pipeline combining sensor data ingestion, anomaly detection, and predictive analytics using Kafka and Spark.

- Achieved over 85% accuracy in failure prediction, proactively guiding maintenance teams, saving an estimated $2M annually.

- ML Frameworks: TensorFlow, PyTorch, Scikit-learn

- Cloud Services: AWS IoT, Azure IoT, Google Cloud IoT, Lambda, Functions

- Protocols & Edge Tech: MQTT, CoAP, OPC UA, TensorFlow Lite, Edge TPU

- Data Storage: DynamoDB, InfluxDB, Hadoop

- Development: Python, C++, Java, Docker, Kubernetes

- Monitoring & Visualization: Grafana, Kibana

- English (Native)

- Spanish (Professional Working Proficiency)