Open to opportunities

Ashton Shungchai Lim

@ashtonshungchailim

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AI/ML Engineer with 5+ years of experience in intelligent systems.

United States

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What I'm looking for

I am looking for a role that fosters innovation, encourages collaboration, and offers opportunities for professional growth in AI and machine learning.

I am an AI/ML Engineer with over 5 years of experience in designing and deploying intelligent systems across healthcare, fintech, and logistics. My expertise lies in translating raw data into impactful solutions, such as detecting early-stage cancer and preventing financial fraud. I am proficient in deep learning, NLP, and MLOps, with a strong focus on explainability, scalability, and production performance.

Throughout my career, I have led the development of an AI platform for early cancer detection, achieving significant improvements in accuracy and trust through explainable models. My work at Grail, Inc. involved collaborating with regulatory and clinical partners to align AI systems with real-world diagnostic workflows. Additionally, I have engineered fraud detection models at Plaid, enhancing accuracy and reducing financial loss, while also automating logistics workflows at Flexport to save substantial labor hours.

I am passionate about making complex machine learning solutions understandable and responsible. I strive to mentor junior engineers and foster best practices in machine learning, ensuring that the solutions I develop are not only effective but also ethical and valuable to users.

Experience

Work history, roles, and key accomplishments

Machine Learning Engineer

Grail, Inc.

Aug 2022 - Feb 2025 (2 years 6 months)

Led development of an AI platform for early cancer detection using genomic and clinical data, reducing false positives by 23% and improving recall by 15%. Designed explainable models with SHAP and LIME to meet FDA interpretability requirements and increase clinical trust.

Genomics SHAP LIME FDA MLOps Apache Airflow

Data Scientist

Plaid

Jul 2019 - Jul 2022 (3 years)

Engineered fraud detection models using behavioral and transaction data, increasing fraud detection accuracy by 38% and reducing financial loss by 22%. Built real-time pipelines for transaction monitoring, flagging fraudulent behavior within seconds with no backend latency.

Fraud Detection Docker Kubernetes Client Side Analytics

Python Developer / Data Scientist

Flexport

Jul 2017 - Jun 2019 (1 year 11 months)

Automated logistics workflows using Python, reducing manual data entry by 70% and saving 200+ labor hours monthly. Built time-series forecasting models for global shipping costs, improving pricing accuracy and boosting client retention by 12%.

Python Time Series NLP Data Quality Shipping Route Optimization

Machine Learning Intern

C3 AI

May 2016 - Aug 2016 (3 months)

Designed anomaly detection algorithms for industrial IoT telemetry, enabling predictive maintenance and reducing downtime. Built preprocessing workflows for high-frequency sensor data, increasing model performance and reliability.

Anomaly Detection Model Findings Communication Data Analysis

Education

Degrees, certifications, and relevant coursework

San Diego State University

Bachelor of Science, Computer Science (AI/ML Focus)

Grade: 3.7 / 4.0

Activities and societies: Relevant Coursework: Machine Learning, Deep Learning, Algorithms, Data Structures, Probability & Statistics

Focused on Artificial Intelligence and Machine Learning, covering core concepts such as deep learning, algorithms, and data structures. Gained a strong foundation in probability and statistics essential for advanced AI/ML applications.