Priya Sharma

Senior Machine Learning Engineer

City, Country | +00 00000 00000 | your.email@example.com | linkedin.com/in/yourname | kaggle.com/yourname

Research & Engineering Summary

Machine learning engineer with 7+ years taking models from research to production in NLP, recommendation and forecasting. Combines solid statistics with MLOps discipline and has published at applied-ML venues.

Technical Stack

Languages: Python, SQL, R, Scala

ML & AI: PyTorch, scikit-learn, XGBoost, Transformers, LangChain

Data & MLOps: Spark, Airflow, MLflow, Feast, Docker

Methods: NLP, RecSys, Time series, Causal inference, A/B testing

Professional Experience

Senior ML EngineerApr 2022 - Present

Quantia AnalyticsCity, Country

Shipped a two-tower retrieval and ranking system that lifted click-through rate by 18% in A/B tests.
Fine-tuned an LLM for support triage with 91% routing accuracy, saving 14 FTE of manual sorting.
Built a feature store and model registry, cutting time from experiment to production from 6 weeks to 5 days.

Data ScientistJun 2019 - Mar 2022

Meridian InsightsCity, Country

Built gradient-boosted demand forecasts for 40k SKUs, reducing stock-outs by 23%.
Designed an experimentation platform with CUPED variance reduction used by 9 product teams.

Data AnalystJul 2017 - May 2019

Northwind ResearchCity, Country

Automated survey analytics in Python and SQL, cutting report turnaround from 5 days to 1.

Models, Research & Publications

Real-time Recommendation EnginePyTorch · Faiss · Kafka

Two-tower retrieval with online re-ranking serving 3k requests/s at a p99 latency of 40 ms.

LLM Support TriageTransformers · LoRA · FastAPI

Fine-tuned a 7B model with guardrails, reaching 91% routing accuracy and running on-prem.

Education

M.Sc., Statistics & Machine Learning2015 - 2017

Sample Institute of Science, Distinction · Thesis: Bayesian methods for sparse demand

Certifications