Siddhesh Girase

Product Engineer

United States5 yrs 11 mos experience
Highly StableAI Enabled

Key Highlights

  • Patent granted for innovative image processing solution.
  • Expertise in AI/ML with end-to-end solution deployment.
  • Hands-on experience in Robotics and Data Analysis.
Stackforce AI infers this person is a Robotics and AI/ML specialist with strong data analysis capabilities.

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Skills

Core Skills

RoboticsInertial NavigationData AnalysisReliability Engineering

Other Skills

AWS SageMakerAlgorithmsAmazon Web Services (AWS)AnalyticsArduinoArtificial Intelligence (AI)CC++Computer VisionControl SystemsData CollectionData StructuresDockerElectronicsElectronics Hardware Design

About

I seek out a plenitude of solutions, to solve a handful of problems! :) Currently working as a Robotics research aide at the Embedded Control and ARMS Lab at Systems and Control Department (SysCon). Research objectives include extension of Strapdown Inertial Navigation Systems for underground pipeline layout estimations. Previously worked as a Lead Python developer specialising in AI/ML software R&D and deployment. I boast to have developed and deployed end-to-end solutions tailored to the business needs of my clients in eCommerce and Tech startups for the last couple of years. My day to day responsibilities also include researching and developing AI/ML POCs and creating business development opportunities especially involving applications related to Large Language Models. NLP, Deep Learning architectures, Generative AI, and Robotics, deeply interest me. I am aware and closely follow developments in LLM frameworks like LlamaIndex, LangChain, Llamaware, etc. I am fond of classical image processing and have worked on various computer vision projects employing varied image pre-processing, augmentation, feature engineering, segmentation, etc. I have hands-on experience with developing and validating classical machine learning models like SVM, Decision trees, Random Forest, Boosted trees etc. I habitually look out for and employ best industrial practices in ML for hyper parameter tuning, pipelining, validation, etc. Currently, I am involved in MLOPs practices leveraging AWS cloud to deploy scalable solutions, with a focus on LLMOps. Also, experienced with data ETL, data visualization and modeling using tools like JMP and Python. I like to represent data in simpler forms to make customer reports as fun as possible while providing key business insights! Studied B.Tech Electronics, 2019 from VIT Pune. Spent my engineering days tinkering on various projects in the fields of Image processing, Robotics, Machine Learning, IoT, etc. Hey, a fellow inventor too! ;) In 2024, received a patent grant for our invention based on Image processing under the title "Local Positioning, Monitoring, Navigation and Path Planning using Computer vision". ------------------- Skills ---------------------- NLP, Computer Vision, Image Processing, Machine learning, AI, Data Science, Function Discovery, Data analytics, Programming, Python, C, C++, Java, Linux, MLOps, Tensorflow, Keras, Neural Networks, Deep learning, ML, Data Structures and algorithms, DSA, LLM, Generative AI, LangChain, LlamaIndex, AWS Cloud, PostgreSQL, Fast API.

Experience

5 yrs 11 mos
Total Experience
1 yr 11 mos
Average Tenure
--
Current Experience

Indian institute of technology, bombay

Research Engineer

Sep 2024Aug 2025 · 11 mos · Mumbai, Maharashtra, India

  • Estimating Pipeline Layout using Inertial Measurement Unit (IMU) readings at ARMS Lab, SysCon dept.
  • Lead by PI: Prof. Dr. Leena Vacchani
Inertial NavigationRoboticsData Analysis

Afour technologies

2 roles

Lead Software Development Engineer

Apr 2024Aug 2024 · 4 mos · Remote

Senior Software Development Engineer

Jan 2023Mar 2024 · 1 yr 2 mos · Remote

  • Probably busy building an ML pipeline..

Seagate technology

3 roles

Engineer II

Aug 2021Jan 2023 · 1 yr 5 mos

Engineer

Jul 2019Aug 2021 · 2 yrs 1 mo

Engineering Intern

Jan 2019Jun 2019 · 5 mos

  • Lead the Data Collection and Analytics strategy for Reliability Testbeds of Seagate Cloud Systems.
  • Formulated test plans in accordance to industry standard reliability practices (MIL-HDBK-781) and enabled test monitoring in form of Live Dashboards.
  • The dashboards are also capable of displaying vivid and insightful telemetry data of temperature, fan speed, workload, etc.
  • Optimised acceleration factors for reliability stress tests.
  • Completed Design for Reliability Training and Six Sigma Green Belt.
Data CollectionAnalyticsReliability TestingData AnalysisReliability Engineering

Education

Georgia Institute of Technology

Master of Science - MS — Robotics

Aug 2025Aug 2027

UC San Diego Extended Studies

Computer Science

Nov 2022Dec 2023

Vishwakarma Institute Of Technology

BTech - Bachelor of Technology — Electronics

Jan 2015Jan 2019

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