Key Strengths

Strong foundation in Machine Learning and Computer Vision, demonstrated by projects like YOLO V5 multi-label classifier and multimodal facial recognition system.
Experience with MLOps concepts, including deploying ML models as microservices, dockerization, and real-time monitoring of asynchronous tasks (Celery, Flower).
Proficiency in data extraction and processing using tools like EasyOCR, Tesseract, and REGEX.
Experience with distributed systems and networking, as shown in the TCP socket-based backup system project.
Exposure to cloud platforms (Microsoft Azure) and logging pipelines (ELK stack).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project diversity, ranging from ML-focused solutions to backend development and distributed systems, indicates adaptability and a broad technical interest. The 'Machine Learning Head' role at a student branch suggests a willingness to contribute to a technical community and mentor others. The target role of ML Engineer aligns well with the candidate's project experience in ML, computer vision, and MLOps. However, the lack of diverse team or company culture exposure beyond internships and academic projects limits a comprehensive cultural fit assessment.

Soft Skills & Operational Fit

The candidate's project descriptions indicate problem-solving skills (automating manual verification, devising backup systems) and a proactive approach (adding fail-safe mechanisms, notifications). Mentoring experience suggests leadership and communication abilities. The Smart India Hackathon win demonstrates teamwork and innovation under pressure. However, without specific psychometric or English test results, a deeper assessment of soft skills and operational fit is limited.

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Aditya Gitte

ML Engineer

https://www.opentalent.in/aditya-gitte

Tech @ General Mills | ex-intern: AI4Bhārat IIT Madras & UST Global | SIH '22 Winner | PICT CE '24

General Mills

Pune, Maharashtra, IndiaMember since June 25, 2026

https://www.opentalent.in/aditya-gitte

About

Currently a Software Engineer at General Mills, I focus on building scalable and efficient software solutions. My background combines practical backend development experience with a deep dive into AI and Deep Learning through academic research and internships. I'm passionate about leveraging emerging AI, like LLMs and agentic systems, underpinned by robust backend infrastructure, to create impactful end-to-end applications.

Top Skills

Computer ArchitectureOperating SystemsDjangoCeleryMicrosoft AzureData StructuresBackend DevelopmentArtificial Intelligence (AI)TensorFlowC++

Skills

Computer ArchitectureOperating SystemsDjangoCeleryMicrosoft AzureData StructuresBackend DevelopmentArtificial Intelligence (AI)TensorFlowC++GitMysqlGithubDockerComputer VisionFlaskComputer Networking

Education

Pune Institute of Computer Technology

Bachelor of Engineering - BE

August 1, 2020 – May 1, 2024

Modern Education Society's Nowrosjee Wadia College Arts, Science, Pune 01

Junior college

July 1, 2017 – March 1, 2020

The Bishop's School, Pune

High School Diploma

June 1, 2008 – May 1, 2017

Experience

General Mills

Software Engineer

July 1, 2024 – Present

Mumbai, Maharashtra, India · Hybrid

AI4Bhārat

Backend Intern

August 1, 2023 – February 1, 2024

PICT CSI Student Branch (PCSB)

Machine Learning Head

May 1, 2023 – May 1, 2024

Pune · On-site

UST

Machine Learning Intern

November 1, 2022 – February 1, 2023

Pune, Maharashtra, India · Remote

Pune Institute of Computer Technology

Research Intern

June 1, 2022 – July 1, 2022

Pune, Maharashtra, India · On-site

Projects

PAN and Aadhar verification and classification using Machine Learning

July 1, 2022 – Present

• This Project won the Smart India Hackathon 2022 • The objective of the project was to automate the verification of Aadhar and Pan card using Machine Learning. This task was primarily completed manually by all the organizations and hence required considerably more time • For the machine learning model we trained a custom YOLO V5 multi-label classifier for the visual verification of Pan and Aadhar • For data extraction we used a combination of EasyOCR and Tesseract which was fine-tuned using Pan number's dataset. REGEX was used to extract useful information. • The ML model was deployed as a micro-service. The entire system was implemented through a dockerized web app. • This webapp had multiple multiple feature like bulk automation, facial recognition based user authentication, admin console, email OTP service, etc.

Certifications

Professional Cloud Architect Certification

Google

June 25, 2026 – Present

Supervised Machine Learning: Regression and Classification

Coursera

June 25, 2026 – Present

Key Strengths

Strong foundation in Machine Learning and Computer Vision, demonstrated by projects like YOLO V5 multi-label classifier and multimodal facial recognition system.
Experience with MLOps concepts, including deploying ML models as microservices, dockerization, and real-time monitoring of asynchronous tasks (Celery, Flower).
Proficiency in data extraction and processing using tools like EasyOCR, Tesseract, and REGEX.
Experience with distributed systems and networking, as shown in the TCP socket-based backup system project.
Exposure to cloud platforms (Microsoft Azure) and logging pipelines (ELK stack).

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit