Chandan Dwivedi

Machine Learning Engineer

Gurugram, Haryana, India6 yrs 1 mo experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in building AI solutions for Cybersecurity.
Proficient in deploying scalable machine learning models.
Strong background in computer vision and deep learning.

Stackforce AI infers this person is a Cybersecurity and AI specialist with a focus on machine learning and computer vision.

Contact

Skills

Core Skills

Machine LearningComputer VisionSoftware Development

Other Skills

Deep LearningREST APIsGraphDBAWSKServeKafkaAirflowNeo4JFlinkNLPC++Face RecognitionDockerKubernetesTensorFlow

About

As a Senior Machine Learning Engineer, working in the Cybersecurity domain, I work on building and deploying impactful and efficient AI models to solve a variety of Cybersecurity and threat hunting problems. I work on crafting AI solutions using Machine Learning, Deep Learning, LLMs and graphs to do threat hunting, cyber attack prevention and containment. I have a solid background in computer science, having graduated with a Bachelor's Degree in Computer Science from Motilal Nehru National Institute Of Technology in 2018. I have extensive experience with various data science tools, frameworks, and technologies, such as TensorFlow, PyTorch, OpenCV, AWS, Flink, Kafka, GraphDB, Neo4j, MLOps, and REST. I have also worked on creating augmented reality (AR) and AI applications by using computer vision and AI/ML techniques, and writing efficient low-level C/C++ codes to create real-time applications and deploy them on edge devices. I am passionate about solving challenging problems and creating value for the users and the business.

Experience

6 yrs 1 mo

Total Experience

1 yr 6 mos

Average Tenure

Current Experience

Zupee

Senior Machine Learning Engineer

Sep 2022 – Sep 2024 · 2 yrs

Improved the performance of the fraud detection system by using Deep Learning and computer vision.
Built and deployed APIs for Machine learning model for serverless inference using KServe. Deployed the APIs in production. Integrated monitoring using Sentry, New Relic, Grafana, and Kafka Logging. Implemented Canary Rollouts and auto-scaling configurations.
Created Model Monitoring pipeline and deployed using Airflow to be executed daily, configured Airflow DAGs and schedule files.
Worked on building the multi-accounting fraud detection system and community detection system using GrpahDB, AWS Neptune, Neo4J, Gremlin, Flink, and Kafka. Currently working on improving the performance by using Graph Neural Networks.
Working with tools like AWS Athena, OpenCV, Pytorch, Tensorflow, Apache Flink, Kafka, etc to build solutions, scale them, and deploy them using CICD, Docker, Kubeflow, and AWS Kubernetes(EKS).

Deep LearningComputer VisionREST APIsGraphDBAWSKServe+3

Fynd (shopsense retail technologies pvt. ltd.)

Senior Software Engineer

Sep 2021 – Sep 2022 · 1 yr

Dec: 2021 to Sept 2022: Leading AI team.
> Implemented media content moderation, recommendation engine, Text moderation using NLP, 3D avatar generation using selfie images, and various other AI features for the E-gaming platform.
> Worked on the complete lifecycle of AI products right from data collection, data cleaning, Model training, tuning, and optimizing to deploying models on AWS Kubernetes pods and/or mobile devices.
Sept. 2021 to Dec 2021: AI/ML, C++ development for Augment Reality applications.
> The project aims at creating an AR experience for the customers to enable them to try out things through the camera in real-time while purchasing.
> I worked on creating efficient C++ pipeline implementations and improving the performance of the platform for the different categories of the product.

NLPC++Machine LearningComputer VisionREST APIs

Deepedge.ai

Machine Learning Engineer

Sep 2020 – Sep 2021 · 1 yr · Hyderabad, Telangana, India

Building and Deploying AI models on Edge Devices.
Implemented Face Recognition pipeline on a camera device(SOC).
Increased the performance of the Face Recognition pipeline by using various preprocessing and post-processing methods.
Implemented efficient, fault-tolerant C++ libraries (.so and .dlls) for Face Registration Engine and used .NET application to call the libraries.

Face RecognitionC++REST APIsMachine Learning

Aiseon healthcare technologies pvt ltd

Software Engineer

Jul 2018 – Aug 2020 · 2 yrs 1 mo · Mumbai Metropolitan Region

Developed a scalable, distributed and asynchronous Rest API for Cognitive models by using Message Broker, Task queue, Gunicorn, Nginx, Docker and Kubernetes.
i. Made it scalable and robust to be able to serve a high number of concurrent demands.
ii. Integrated Continuous Integration and Continuous Delivery and database auditing using MongoDB.
Redesigned the Job orchestration and pipeline to process data, train networks and generate results by using IBM-Cloud Bare Metal Servers, Spark MLlib, IBM-Cloud Python runtime, TensorFlow, and OpenCV.
Developed new features for data annotation tools to make annotation easy and more automatic using Neural networks, clustering algorithms, segmentation models, multithreading, and multiprocessing.
Implemented A/B Testing using Kubernetes canary deployment.
Increased performance of AI platform by 20% by using hybrid, scalable and decoupled neural network models.

REST APIsDockerKubernetesTensorFlowOpenCVSoftware Development