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Sam Alam

@samalam

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Senior AI/ML Data Scientist specializing in scalable Generative AI, fraud detection, and MLOps.

United States

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What I'm looking for

I’m looking to build and scale production Generative AI and ML systems end-to-end—model lifecycle, monitoring, and governance included—where I can improve reliability (latency, drift, safety) and deliver measurable business impact in regulated settings.

I’m a Senior AI/ML Data Scientist with 9+ years of experience building and scaling production-grade machine learning systems across healthcare, financial services, and enterprise SaaS. I turn complex analytical challenges into scalable, reliable, and compliant AI—especially in regulated environments.

In my current role as Lead AI/ML Engineer at Cloudera, I led the design and production rollout of enterprise AI systems for clinical analytics and knowledge platforms. I architected modular RAG systems, improved monitored deployment stability, and optimized transformer inference (LoRA fine-tuning, quantization, GPU tuning) to meet 100ms latency SLAs while reducing cost. I also established drift detection, telemetry monitoring, CI/CD workflows, and SHAP-based explainability dashboards to strengthen audit transparency.

Previously at DataRobot, I led fraud detection and risk scoring that reduced false positives, built time-series forecasting to improve planning accuracy, and implemented A/B testing, uplift modeling, and causal inference for revenue-driven decisions. Earlier at Uniphore, I developed NLP intent classification and sentiment analysis, built REST inference services, and automated ETL pipelines to improve availability and reliability. My work consistently emphasizes end-to-end model lifecycles—from experimentation and modeling to deployment, monitoring, and governance.

Experience

Work history, roles, and key accomplishments

Current

Lead AI/ML Engineer

Current

Cloudera

Oct 2023 - Present (2 years 8 months)

Led design and production rollout of enterprise AI for clinical analytics, including standardized healthcare data models, APIs, and monitored ML pipelines. Architected RAG systems to reduce hallucinations, optimized LoRA/quantized transformer inference to meet 100ms latency SLAs, and implemented drift monitoring, SHAP explainability, and ML CI/CD with MLflow.

RAG Transformer Inference Optimization Kubernetes MLFlow Monitoring For Drift SHAP Explainability

Senior Data Scientist

DataRobot

Mar 2020 - Sep 2023 (3 years 6 months)

Developed fraud detection and risk scoring models on large transaction datasets, reducing false positives, and built time-series forecasting for financial planning and demand prediction. Designed A/B testing, uplift modeling, and causal inference frameworks, engineered Spark/SQL feature pipelines, and productionized containerized ML APIs with SHAP explainability for regulatory audit readiness.

Fraud Detection Time Series Models A B Testing Uplift Models Causal Inference SHAP Containerized ML APIs

Machine Learning Engineer

Uniphore

Jul 2017 - Feb 2020 (2 years 7 months)

Built NLP models for intent classification and sentiment analysis for enterprise conversational AI platforms. Developed scalable preprocessing and feature engineering workflows, automated ETL for structured and unstructured data, and delivered REST-based inference services while optimizing architectures to reduce compute utilization and improve monitoring for stable production deployments.

NLP Sentiment Analysis Feature Engineering ETL Optimization ML Evaluation And Monitoring Conversational AI