Mohit G.

Software Engineer

New York, New York, United States10 yrs 8 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Led migration of SSO SAML certificates at Salesforce.
Developed BlazingMQ outperforming Kafka and RabbitMQ.
Designed GDPR-compliant algorithms for unstructured data.

Stackforce AI infers this person is a SaaS and Fintech software engineer with expertise in Big Data and machine learning.

Contact

mohitgupta277@gmail.com LinkedIn

Skills

Core Skills

JavaBig DataC++Pl/sqlPython

Other Skills

AWSAlgorithmsAndroidApache KafkaApache TikaCC#CSSCore JavaData StructuresDistributed ComputingDistributed SystemsDockerEclipseFlume

About

Loves Computer Science! Some of my projects have been open sourced and can be looked up at my github page. These include code for research work on shallow discourse parsing, text recognition, named entity recognition and intrusion detection. https://github.com/mohiitgupta #boilerup

Experience

10 yrs 8 mos

Total Experience

2 yrs 2 mos

Average Tenure

4 yrs 9 mos

Current Experience

Salesforce

Lead Software Engineer

Sep 2021 – Present · 4 yrs 9 mos · New York, New York, United States

Customer Identity and Access Management (CIAM) inside Marketing Cloud.
Led initiative to migrate customers using older SSO SAML certificates to newer ones without getting impact to their business seamlessly using a data-driven approach.
Designed and implemented support for Customer selected Signing Algorithm for SAML AuthNRequests sent by Salesforce Marketing Cloud Service Provider (SP) in SP-init based SSO Logins to IDPs.
Designed and implemented throttling mechanism for User Login, Reset Password flows.
Revamped the onboarding experience for new hires to CIAM. This includes demo guides, docs to help new engineers join seamlessly to the team. Mentored 2 engineers to successfully onboard using the revamped experience.
Exposure: Java, Spring Web Flow, C#, Docker, Kubernetes, K9s, Helm, SQL, Redis, AWS, Spinnaker

JavaSpring Web FlowC#DockerKubernetesK9s+6

Bloomberg lp

Software Engineer

Jun 2019 – Sep 2021 · 2 yrs 3 mos · New York, New York, United States

Development of BlazingMQ. A distributed message queuing system which outperforms several standard open source frameworks like Kafka, RabbitMQ in performance and resiliency.
More details can be found at https://github.com/bloomberg/blazingmq
My main contributions included:
Message Compression
Cluster State Management
Exposure: C++, Distributed Systems

C++Distributed SystemsBig Data

Informatica

Machine Learning Intern

May 2018 – Aug 2018 · 3 mos

Part of the Product Incubation Lab at Informatica. Worked on the design, development and implementation of Subject Indexing on unstructured data as a step towards helping Informatica's clients become GDPR compliant. My main contribution was the design and implementation of a novel algorithm based on "Semantic Cohesion".
Exposure: Java, Stanford CoreNLP toolkit, OpenNLP, Apache Tika, Distributed Computing

JavaStanford CoreNLPOpenNLPApache TikaDistributed ComputingBig Data

Purdue university

Graduate Research Assistant

Aug 2017 – May 2019 · 1 yr 9 mos

Part of the Information Management and Analysis Group at Purdue. The aim was to design, develop and implement new features inside Graduate School Database to manage student information.
Exposure: PL/SQL, CSS, PHP

PL/SQLCSSPHPBig Data

Visa

Software Engineer

Aug 2015 – Jul 2017 · 1 yr 11 mos

Part of the Visa Developer Platform Team. This team aims to make life of the developer community easier by providing APIs for Visa Product Families. I designed and built RESTful web services in Java and wrote python SDK for Visa Direct. Also built a reporting infrastructure inside Visa platform for Business analytics and Real-time monitoring.
Exposure: Java, Spring, SQL, Oracle DB, Mongo DB, Python, Javascript, Kafka, Flume, Hadoop, Kibana, Tableau

JavaSpringSQLOracle DBMongo DBPython+7

École normale supérieure

Machine Learning Researcher

May 2015 – Jul 2015 · 2 mos

Identified and differentiated between badly segmented and correctly segmented corpora using machine learning. The aim was to identify all the colloc levels using an unsupervised method i.e. with the notion of Self Consistency (based on Latent Semantic Analysis).
Wrote a blog post about it here http://bootphon.blogspot.com/2015/08/identifyingadequate-level-of.html
Exposure: Python, Scripting, nltk, numpy, scipy

PythonScriptingnltknumpyscipyBig Data

Amazon

Software Developer Intern

May 2014 – Jul 2014 · 2 mos

As part of the Address Technology Team, Worked on CASS Certification of the present Amazon Address Validation Expert System (AVES) for North America.
Also designed a prototype to support future work on designing an AVES for India
Exposure: Java, Maven, Spring, Lucene, Luke, Git

JavaMavenSpringLuceneGitBig Data

Inoxapps

Software Developer Intern

May 2013 – Jul 2013 · 2 mos

The work involved developing an android application and working on the NDK library. The application was developed with the use of fragments and handlers were used to control the lifecycle and to execute runnables in the app.