Open to opportunities

preethi marri

@preethimarri

Message

Senior MLOps engineer building compliant, low-latency ML platforms on GCP and AWS.

United States

Message

What I'm looking for

I’m looking to build production MLOps/LLM systems with strong observability, governance, and low-latency performance—partnering with ML, security, and product teams to continuously improve models and ship reliable outcomes in regulated environments.

I’m a Senior MLOps Engineer with 7+ years building and operating production ML platforms on GCP and AWS, end-to-end from data ingestion and feature engineering to training, evaluation, deployment, and monitoring.

At Equifax, I designed and operated Vertex AI model lifecycle workflows (pipelines, endpoints, and model registry), improving time-to-production for new models by ~40%. I also reduced model inference latency by 100ms to meet enterprise SLAs.

I’m especially proud of my focus on reliable, secure, and compliant systems in regulated environments—leveraging audit logs, encryption, IAM, and PII handling (including CCPA/GDPR considerations). I implement observability and drift monitoring with Evidently AI, Deepchecks, TensorFlow Data Validation, and Datadog, backed by actionable KPIs in Looker.

I’ve also delivered engineering platforms that help teams move faster, including CI/CD for ML (Jenkins, GitHub Actions), Docker/Kubernetes-based production serving, and a Django-based internal model configuration platform for versioning and deployment. I’ve even built a proof-of-concept LLM pipeline from internal log data to explore evaluation, prompt management, and production-oriented deployment patterns.

Experience

Work history, roles, and key accomplishments

Current

Machine Learning Engineer

Current

Equifax, Inc.

Nov 2023 - Present (2 years 7 months)

Designed, deployed, and operated production ML systems on GCP using Vertex AI pipelines, endpoints, and model registry, reducing time-to-production for new models by ~40%. Implemented monitoring and observability (Evidently AI, DeepChecks, TensorFlow Data Validation, Datadog) and optimized online serving to reduce inference latency by 100ms while meeting enterprise SLA thresholds.

Vertex AI Model Monitoring ML Model Registry CI CD For ML Docker Observability Evidently AI

Software Engineer / Data Engineer

EA Sports, Inc.

Oct 2021 - May 2023 (1 year 7 months)

Designed and maintained an AI/ML platform on Amazon SageMaker that enabled data scientists to train, evaluate, and deploy models with reduced engineering dependency and faster delivery. Built production REST APIs and end-to-end data pipelines (S3, PostgreSQL, Snowflake) and implemented CCPA/GDPR-compliant tokenization with audit logging, encryption, and PII handling.

Amazon SageMaker REST APIs Python Flask Data Pipelines AWS Lambda Snowflake PostgreSQL CCPA GDPR Tokenization Data Governance

Software Engineer / Data Engineer

Archimed

Jul 2019 - Aug 2021 (2 years 1 month)

Built ML model serving infrastructure and REST APIs with Flask and Pandas to enable business teams to self-serve web traffic insights. Created automated data ingestion and big data processing pipelines (HDFS, Hive, Sqoop, Pig) and developed an end-to-end recommendation model for suggesting student peer connections.

Flask Python HDFS Hive Sqoop Pig Data Pipelines

Software Engineer

ITS Cybertech India Pvt Ltd

Jan 2017 - May 2019 (2 years 4 months)

Developed full-stack Python/Django web applications across the software development lifecycle for multiple enterprise clients. Designed Informatica ETL pipelines into an Oracle Data Warehouse, tuned workflows to reduce processing time for high-volume loads, and delivered unit tests and technical documentation with PyTest.