Open to opportunities

Adithya Raj

@adithyaraj

Machine Learning Engineer building AWS production fraud and forecasting systems with agentic AI, MLOps, and measurable impact.

Canada

Message

What I'm looking for

I’m looking to build and deploy production ML systems on AWS—agentic/LLM workflows included—with strong MLflow auditability, monitoring, and low-cost performance through reliable CI/CD and serverless design.

I’m a Machine Learning Engineer focused on shipping production ML that holds up in real-world conditions. I built and delivered two AWS systems—FraudLens and StockSenseAI—where I combined agentic AI workflows, strong model explainability, and cost-aware serverless deployment.

In FraudLens, I diagnosed and fixed label leakage that inflated results, retraining to honest production metrics (92.1% F1, 89.9% recall) with full MLflow auditability. I also led delivery of production-grade pipelines and REST APIs at Queen’s University Student Consultancy, improving end-to-end latency by 35% and reducing manual ops work by ~8 hrs/week through CI/CD-gated ETL data-quality assertions.

Experience

Work history, roles, and key accomplishments

Lead Software Developer

QWeb -- Queen's University Student Consultancy

Sep 2022 - Apr 2026 (3 years 7 months)

Improved end-to-end response latency by 35% across production data pipelines serving 500+ users by profiling async workflow bottlenecks and validating fixes with automated smoke tests. Reduced manual ops work by ~8 hrs/week by designing ETL pipelines with data-quality assertions integrated into CI/CD gating, and shipped 2 production REST APIs with structured MongoDB schemas and Git-based release w

Async Workflow Profiling Smoke Testing ETL Type Mismatches)CI CD REST APIs

Machine Learning Developer (Co-op)

Brain Toy

Feb 2021 - Jun 2021 (4 months)

Developed a breast cancer prediction ML model achieving 82% classification accuracy using cross-validation. Built an automated Python ETL pipeline that reduced preprocessing time by 40% across 100K+ records and integrated it into a clinical decision-support tool.

Python Machine Learning Cross Validation Model Development ETL data preprocessing

Education

Degrees, certifications, and relevant coursework

Queen's University

Bachelor of Computer Science (Honours), Computer Science (AI Specialization)

2022 - 2026

Activities and societies: Relevant coursework: Machine Learning, Deep Learning, NLP, Computer Vision, Data Mining, Statistical Inference, Cloud Computing, Software QA. Co-authored an IEEE-format research paper on rideshare tipping behavior.

B.Comp. (Honours) in Computer Science with an AI specialization. Completed coursework across machine learning, deep learning, NLP, computer vision, data mining, statistical inference, cloud computing, and software QA.