Open to opportunities

Benjamin Ross

@benjaminross

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AI/ML Engineer with 8+ years of experience in machine learning.

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 8 years of experience in delivering production-grade machine learning systems across diverse sectors including healthcare, cybersecurity, and e-commerce. My expertise lies in transforming data into intelligent, explainable, and scalable systems. I have a proven track record of deploying ML models at scale using modern MLOps tools and practices, ensuring regulatory compliance while enhancing cross-functional collaboration.

In my most recent role as a Senior Machine Learning Engineer at Tech Insights, I engineered multi-modal ML models for cancer prognosis, significantly improving prediction accuracy and treatment outcomes for over 100,000 patients annually. My work in building explainable AI interfaces has fostered trust in clinical decision support tools, while my automation of deployment workflows has reduced release times by 35%. I am passionate about mentoring junior engineers and leading architecture reviews to promote scalable system design.

Throughout my career, I have consistently delivered impactful solutions, such as real-time threat detection models at CrowdStrike and fraud detection systems at Plaid, which have enhanced security and reduced financial losses. I thrive in collaborative environments and am dedicated to driving business impact through innovative AI solutions.

Experience

Work history, roles, and key accomplishments

Senior Machine Learning Engineer

Tech Insights

Aug 2022 - Present (2 years 10 months)

Engineered multi-modal ML models for cancer prognosis using genomic and imaging data, improving prediction accuracy by 19%. Built explainable AI interfaces (SHAP, Integrated Gradients) used in FDA-compliant clinical tools, increasing clinical trust in decision support tools.

Machine Learning Deep Learning Explainable AI MLOps Mentorship

Machine Learning Engineer

CrowdStrike

Jul 2019 - Present (5 years 11 months)

Built real-time threat detection models from telemetry logs, improving malware detection precision by 31%. Deployed anomaly detection pipelines for endpoint protection, identifying breaches in real-time and ensuring system integrity.

Machine Learning Anomaly Detection Real Time Systems Endpoint Protection System Security

Machine Learning Engineer

Plaid

Jul 2017 - Present (7 years 11 months)

Developed fraud detection models using transactional data, improving detection precision by 25%. Built data pipelines using PySpark for transaction monitoring and anomaly detection, ensuring real-time fraud detection.

Fraud Detection Pyspark Docker Kubernetes Data Pipelines Anomaly Detection Transaction Monitoring Scalability High Availability

Data Science Intern

ZS Associates

May 2016 - Present (9 years 1 month)

Developed patient segmentation models for pharmaceutical clients using claims data, improving targeting of healthcare interventions. Built forecasting models for medication adherence, helping optimize treatment plans and reduce patient non-compliance.

Segmentation Forecast Modelling Data Analysis Dashboards Healthcare Analytics Claims

Education

Degrees, certifications, and relevant coursework

University of Illinois Urbana-Champaign

B.S. in Computer Engineering, Computer Engineering

Grade: 3.8 / 4.0

Activities and societies: Relevant Coursework: Machine Learning, Data Mining, Statistical Inference, Systems Programming

Focused on Machine Learning and Data Science, gaining expertise in core concepts and applications. Completed relevant coursework in Machine Learning, Data Mining, Statistical Inference, and Systems Programming.