Raghav Mantri

Senior Software Engineer

New York, New York, United States7 yrs 5 mos experience

Most Likely To Switch

Key Highlights

Expert in building scalable, low latency applications.
Proficient in machine learning and algorithm development.
Experience in healthcare and fintech sectors.

Stackforce AI infers this person is a Backend-heavy Software Engineer with expertise in Healthcare and Fintech.

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Skills

Core Skills

PalantirSoftware As A Service (saas)Distributed SystemsLow LatencyAlgorithm DevelopmentMachine Learning

Other Skills

PySparkjavaBusiness AnalysisPython (Programming Language)TypeScriptFoundryData AnalysisAnalytical SkillsAerospikeGoogle Kubernetes Engine (GKE)AlgorithmsSystems DesignGo (Programming Language)Apache KafkaHive

About

Started my journey as a research engineer. Developed a knack for detail, persistence, and confidence to attack unexplored problems. Then tried my hands at backend engineering to learn how to build a complete product. Have been fortunate to work on a highly scalable, low latency, and rapidly evolving product. Always on the lookout for challenging work that I can contribute to as well as learn from.

Experience

7 yrs 5 mos

Total Experience

1 yr 10 mos

Average Tenure

2 yrs 1 mo

Current Experience

Capital one

Senior Software Engineer

May 2024 – Present · 2 yrs 1 mo · New York City Metropolitan Area · Hybrid

Palantir technologies

Software Engineer

Aug 2022 – Jul 2023 · 11 mos · London, England, United Kingdom

Built applications for the NHS. Tech Stack: Typescript, Pyspark, Python, Palantir Foundry

PalantirPySparkjavaSoftware as a Service (SaaS)Business AnalysisPython (Programming Language)+5

Media.net

2 roles

Software Engineer II

Jan 2021 – Aug 2022 · 1 yr 7 mos

Migrated bidder from monolithic architecture to containerized service oriented architecture (SOA).

javaAerospikeLow LatencyGoogle Kubernetes Engine (GKE)Python (Programming Language)Algorithms+8

Software Development Engineer

Dec 2019 – Jan 2021 · 1 yr 1 mo

Building the real-time bid prediction algorithm for programmatic advertising in a high throughput (300k QPS) and low latency (5ms) system.
Tech Stack: GoLang, Java, Python, Aerospike DB, Apache Kafka, Kubernetes, Google Cloud Platform (GCP), Some machine learning libraries (Catboost, xLearn, OpenAI)

javaAlgorithm DevelopmentApache KafkaKubernetes

American express

2 roles

Research Engineer

Jul 2018 – Nov 2019 · 1 yr 4 mos · Bengaluru Area, India

Research Engineer in Artificial Intelligence Labs (formerly Big Data Labs) of Amex. Worked on gradient boosting machines (XGBoost).
Researched and developed data-driven techniques to make gradient boosting online to capture seasonal trends in fraud detection.
Researched and implemented new features and enhanced existing features in Amex specific implementation of XGBoost.
Tech Stack: C++, Bash, Python

C++XGBoostCatboostC++ ProgrammingOpenMPMachine Learning Algorithms+3

Research Intern

Jan 2018 – Jun 2018 · 5 mos · Bengaluru Area, India

Worked in Big Data Labs, AMEX, Bengaluru. Researched and implemented different algorithms to make the Gradient Boosting Machines (XGBOOST) online, for the purpose of Fraud Detection.

Algorithm Design

Microsoft

Software Engineer Intern

Jun 2017 – Jul 2017 · 1 mo · Hyderabad Area, India

Worked in Microsoft IDC, in OneNote for Android team. Evaluated different frameworks available for hosting contextual online surveys and integrated the selected framework.

java

Tata institute of fundamental research, mumbai

Research Intern

May 2016 – Jul 2016 · 2 mos · Mumbai Area, India

Mail Input Output
Worked on server automation, in order to provide users the facility to update and make additions to the platform MetaStudio by just sending a mail to a particular email address.