Open to opportunities

Ashutosh Bharambe

@ashutoshbharambe

Message

Machine Learning Engineer with expertise in deep learning and software development.

Zimbabwe

Message

What I'm looking for

I seek a role that fosters innovation, collaboration, and continuous learning in machine learning.

I'm a Machine Learning Engineer currently working at DyadAI - JuliaHub Inc., where I implement innovative deep learning methods for complex dynamical systems. My journey in technology began at the Indian Institute of Technology Roorkee, where I earned my BTech in Electronics and Communications Engineering with a CGPA of 8.7. During my studies, I developed a strong foundation in machine learning and software engineering, which I have applied in various internships and projects.

At Cisco Systems, I interned as a Software Engineer, where I created a method for router failure prediction, showcasing my ability to leverage data for impactful solutions. My contributions to open-source projects, such as adding features to the Julia Symbolics ecosystem during Google Summer of Code, reflect my commitment to advancing technology and my passion for collaborative development. I have also worked on several personal projects, including a mobile app for identifying Indian food items and a web application for performance benchmarking, which demonstrate my versatility and technical skills.

Experience

Work history, roles, and key accomplishments

Current

Machine Learning Engineer

Current

DyadAI - JuliaHub Inc.

Jun 2022 - Present (3 years 2 months)

Implemented novel production-grade deep learning methods for surrogate modeling of continuous-time dynamical systems and stiff differential equations. Developed experiment tracking workflows in Julia with MLFlow and improved performance for model calibration workflows in Dyad AI.

Deep Learning Surrogate Modeling Julia MLFlow

Student Developer

NumFOCUS

May 2021 - Present (4 years 3 months)

Added symbolic integral and its numerical evaluations to the Julia Symbolics ecosystem. Also added support for integro-differential equations to the Physics-Informed Neural Network Solver (PINN).

Julia Symbolic Computation Numerical Methods

Software Engineer Intern

Cisco Systems

Mar 2021 - Present (4 years 5 months)

Developed a novel and computationally efficient method for router failure prediction by analyzing intrinsic router parameters. Leveraged entropy-based metrics to identify precursors to failure.

Router Failure Prediction Data Analysis Entropy Based Metrics Network Engineering Software Development

Student Developer

Julia Seasons of Code

Jun 2020 - Present (5 years 2 months)

Implemented a solver for Kolmogorov Equations, including applications like Black-Scholes and Fokker Planck. Also developed a solver for optimal stopping time problems, such as pricing American Options.

Julia Kolmogorov Equations Black Scholes Pricing Fokker Planck Optimal Stopping Time Problems

Education

Degrees, certifications, and relevant coursework

Indian Institute of Technology Roorkee

BTech., Electronics and Communications Engineering

2018 - 2022

Grade: 8.7 / 10

Activities and societies: Cinematic Section - Secretary, Director, Writer; Standup Club - Joint Secretary, Performer; SDSLabs - Member

Completed a Bachelor of Technology in Electronics and Communications Engineering. Achieved a CGPA of 8.7 out of 10, demonstrating strong academic performance in the field.