Dheeraj B.

Currently working as a freelancer with primary focus on backend and data. As an engineer with strong fundamentals and proven capability in adapting to unfamiliar technologies, I am also looking for opportunities in newer technologies which are not listed above in my profile.

Responsibilities

• Individually research and implement high quality solutions in extremely short deadlines in varied domains such as devops, IoT (Raspberry Pi 3), and cloud APIs in Python-Flask hosted in AWS

Technologies: Python, GItlab CI/CD, Git, Flask, AWS, AWS IoT Core, Raspberry Pi 3, Wiregaurd VPN protocol, Networking

Responsibilities

In my current role, I oversee all facets of technical solution design, development, and implementation. I guide team members to ensure adherence to performance metrics and overarching organizational goals. I leveraged LINQ and LIQ2Couchbase in daily operations.

• Oversaw C# and Agile two-week releases with TDD
• Architected an innovative, scalable solution to provide custom rates for 6,000 loads for 8,000 carriers per day with a throughput of 1,000+ prices provided per minute
• Architected a custom rules engine increasing precision of XPO's ML regression model, enabling custom markups based on various parameters like lane, equipment, and time left for pickup
• Implemented solutions during COVID market disruptions to contribute to maintaining and enhancing top line growth

Technologies: C#, REST, Git, Microservices, Solution Architecture, Rule Engines, .NET Core, Couchbase

Responsibilities

I managed Python data engineering, using various approaches for data cleansing and imputation, including mean and median imputation and K-nearest neighbors. I developed impact analysis of various data inputs into the algorithm, determining usefulness in predicting market rate. I also researched patterns of parameters, including ‘time left for pickup" on final rate and implemented data pipeline based on results.

• Created machine learning pipelines and models based on documentation and requirements from data scientists.
• Reduced response time from 600ms to 300ms by optimizing Python flask API extensively with precision use of multithreading.
• Improved performance by 90% by designing and building custom thread pool mechanism for a requirement, which could not be solved using libraries
• Created a radius based historic search for shipments using It-Ion information available in Elasticsearch

Technologies: Python, Git, Flask, Pandas, Numpy, Scikit-learn, XGBoost

Responsibilities

Here, I facilitated back-end engineering for C# and Agile two-week releases, and unit testing.

• Implemented the backend of available loads functionality end-to-end on V-1.0 of XpoConnect; created multiple scheduled jobs, ensuring effective load and performance of interconnected systems.
• Ideated and implemented two-machine learning based POCs without using cloud services.

Technologies: C#, REST, Git, Microservices, Unit testing, TDD, .NET Core, MS SQL Server, RASA NLU, Chatbots, Tensorflow

Responsibilities

In this role, I automated tasks using JAVA, reading data from a web page, copying and parsing an Excel file in a remote service, connecting to DB and collating data, disseminating results in an email.
 

• Built an automation dashboard (web application) using JQuery, Bootstrap, and JS to allow users to access tools.