Journal of Applied Machine LearningSpecial Issue · Senior Machine Learning EngineerVol. 08 · 2026

Priya
Sharma

Statistician by training, ML engineer by trade.your.email@example.com - +00 00000 00000
PHOTO

At a Glance

Based inCity, Country
Kagglekaggle.com/yourname

The 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

Certifications

Google Cloud Professional Machine Learning Engineer (2023)
AWS Certified Machine Learning - Specialty (2021)

Abstract

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.

“Lifted click-through rate by 18% with a recommender serving 12 million users.”

Findings: Experience

Senior ML Engineer

Quantia Analytics · Apr 2022–Present
  • 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.

Data Scientist

Meridian Insights · Jun 2019–Mar 2022
  • 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 Analyst

Northwind Research · Jul 2017–May 2019
  • Automated survey analytics in Python and SQL, cutting report turnaround from 5 days to 1.

Papers & Models

Real-time Recommendation Engine

PyTorch · Faiss · Kafka

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

LLM Support Triage

Transformers · LoRA · FastAPI

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

Education

M.Sc., Statistics & Machine Learning

Sample Institute of Science · 2015 - 2017