Dikshith Reddy Macherla

About

I’m a Machine Learning & MLOps Engineer focused on shipping models to production., reliably, measurably, and at scale. I design end-to-end systems: data pipelines → model training → API serving → monitoring in the cloud. Currently completing a B.Sc. (Honours) in Computer Science (Data Analytics) at Trent University. I’ve co-authored an IEEE/ACIS SNPD 2025 paper on intraday forecasting and led an award-winning hackathon project (Best AI Project). Toolbox: ML & Data: Python, scikit-learn, XGBoost, TensorFlow, PyTorch, Pandas MLOps/Deploy: FastAPI, Docker, Kubernetes, MLflow, CI/CD (GitHub Actions), AWS (S3/EC2/Lambda, SageMaker), GCP Vertex AI Data Eng: Airflow, Kafka, Spark; DBs: PostgreSQL, MongoDB, Redis NLP/LLMs: Hugging Face, LangChain, FAISS/Pinecone Web: React/Next.js, Uvicorn, Pydantic I care about production impact—latency, cost, reliability, and business metrics. Recent work includes high-frequency time-series forecasting (R²≈0.98), realtime transcription tooling, and full-stack ML demos. Open to: Machine Learning Engineer • MLOps Engineer • Applied AI roles in Toronto/Canada. Portfolio: dikshithreddy.vercel.app | GitHub: github.com/dikshithreddym | Email: dikshithreddymach

Experience

Education