Experienced Engineer Resume Example

Senior AI/ML Engineer · NVIDIA

Seattle, WA · 2023 - Present

• Led the development of an edge AI platform for industrial IoT, resulting in a 40% reduction in data transfer costs and 25% faster inference times for manufacturing clients.
• Designed and implemented real-time computer vision pipelines using NVIDIA Jetson and TensorRT, improving defect detection accuracy by 18% and throughput by 15% on production lines.
• Mentored a team of 4 junior AI engineers, guiding them in deploying optimized machine learning models on constrained hardware and contributing to a 30% increase in team productivity.
• Collaborated with product teams to define AI features for new industrial robotics applications, influencing product roadmap decisions that secured 3 major client contracts totaling over $5M.
• Developed custom CUDA kernels to accelerate critical deep learning operations, achieving a 10-12x speedup compared to standard implementations for specific industrial use cases.

AI/ML Engineer · Siemens Digital Industries

Plano, TX · 2019 - 2023

• Developed and deployed predictive maintenance models for industrial machinery, reducing unplanned downtime by 20% across 5 large-scale manufacturing facilities.
• Engineered anomaly detection systems for SCADA data, identifying critical equipment failures 72 hours in advance with a false positive rate below 5%.
• Optimized existing ML models, achieving a 15% improvement in inference speed and a 10% reduction in memory footprint on embedded controllers.
• Designed and implemented data ingestion pipelines for sensor data from industrial assets, processing over 1TB of time-series data daily with 99.9% uptime.

Junior AI Engineer · Industrial AI Solutions

Boston, MA · 2016 - 2019

• Built and validated initial machine learning models for visual inspection tasks, improving accuracy by 12% over traditional methods for a key client.
• Contributed to the development of data preprocessing pipelines for industrial sensor data, handling diverse data formats and ensuring data quality for model training.
• Assisted in integrating AI models into existing SCADA systems, demonstrating real-time inference capabilities that reduced manual inspection time by 10%.

M.S. in Robotics · Carnegie Mellon University

Pittsburgh, PA · 2014 - 2016

• Specialized in Machine Learning, Computer Vision, and Real-time Systems for robotic applications.
• Thesis: 'Real-time Object Detection for Robotic Pick-and-Place in Unstructured Industrial Environments' achieved 95% accuracy and 30ms latency.
• Maintained a GPA of 3.9/4.0, consistently recognized on the Dean's List for academic excellence.

B.S. in Computer Engineering · University of Illinois Urbana-Champaign

Urbana, IL · 2010 - 2014

• Focused on data structures, algorithms, digital system design, and embedded systems.
• Developed a capstone project 'Optimizing Neural Network Inference on Low-Power Embedded Devices,' reducing power consumption by 25%.
• Graduated Magna Cum Laude with a GPA of 3.7/4.0, demonstrating strong foundational knowledge in computing principles.

Senior Software Engineer · IBM

Cambridge, MA · 2022 - Present

• Led a team of 4 engineers in developing a new cloud-native data orchestration platform, reducing data processing time by 25% and increasing system scalability by 40% to handle peak loads.
• Architected and implemented critical microservices using Go and Kubernetes, improving API response times by an average of 18% and achieving 99.99% uptime for core services.
• Spearheaded the integration of AI/ML models into existing product lines, resulting in a 15% uplift in user engagement and generating an estimated $2M in new annual revenue.
• Mentored junior engineers, conducting code reviews and workshops on best practices, which led to a 10% reduction in production bugs and accelerated feature delivery cycles.

Software Engineer · Raytheon Technologies

Andover, MA · 2019 - 2022

• Developed robust C++ applications for real-time sensor data processing, improving data throughput by 30% and reducing latency for critical defense systems.
• Contributed to the design and implementation of a secure distributed communication protocol, ensuring data integrity and confidentiality for sensitive information exchanges, achieving 100% compliance with security standards.
• Automated build and deployment pipelines using Jenkins and Python scripting, decreasing release cycle times by 20% and reducing manual errors by 50%.

Data Scientist · Thermo Fisher Scientific

Boston, MA · 2016 - 2019

• Developed predictive models using Python (Scikit-learn, TensorFlow) to forecast laboratory equipment failure rates, achieving 92% accuracy and enabling proactive maintenance that saved the company $1.5M annually.
• Designed and implemented A/B testing frameworks for optimizing user interfaces on scientific instruments, leading to a 10% improvement in user efficiency and satisfaction.
• Processed and analyzed large-scale genomic datasets (terabytes) to identify novel biomarkers, contributing to two published research papers and accelerating drug discovery pipelines by 6 months.

Master of Engineering (M.Eng.) in Computer Science · Massachusetts Institute of Technology (MIT)

Cambridge, MA · 2018 - 2020

• Specialization: Distributed Systems and Machine Learning Engineering
• Relevant Coursework: Advanced Algorithms, Operating Systems, Machine Learning, Cloud Computing, Database Systems
• Thesis: 'Optimizing Real-time Data Stream Processing for Anomaly Detection' developed a novel algorithm improving detection speed by 15%.

Bachelor of Science (B.S.) in Applied Mathematics · Boston University

Boston, MA · 2012 - 2016

• Graduated Magna Cum Laude with a GPA of 3.8/4.0
• Relevant Coursework: Numerical Analysis, Probability and Statistics, Differential Equations, Computational Methods, Discrete Mathematics
• Dean's List all semesters; received departmental award for undergraduate research in predictive modeling.