Saqib Azim

Product Manager

San Francisco, California, United States7 yrs 6 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Expert in Machine Learning and Computer Vision.
Proven track record in AI research and development.
Strong academic background with multiple research awards.

Stackforce AI infers this person is a Machine Learning Engineer with expertise in AI and Computer Vision.

Contact

azimsaqib10@gmail.com LinkedIn

Skills

Core Skills

Machine LearningDeep LearningAdversarial AnalysisComputer VisionRoboticsText RecognitionAutonomous Driving

Other Skills

ResearchMatplotlibDeep Reinforcement LearningPython (Programming Language)CUDARobosuiteInverse RLPyTorchOptimizationScikit-LearnTensorFlowExplainable AINumPyMachine Learning AlgorithmsSoftware Development

About

My name is Saqib Azim, and I am currently a Machine Learning Engineer at the San Diego Supercomputer Center. During my Master's studies at UC San Diego, I worked as a Graduate Student Researcher in the Existential Robotics Lab at the Contextual Robotics Institute, under the supervision of Prof. Nikolay Atanasov. Before joining UCSD, I was an Assistant Researcher in the Intelligent Vision Research Group at Hitachi Central Research Lab in Tokyo, Japan, advised by Dr. Katsuyuki Nakamura. My research interests include Robotic Perception and Manipulation, Deep Learning, and Computer Vision. I completed my B.Tech in Electrical Engineering with a minor in Computer Science from IIT Bombay, where I received Undergraduate Research Award in 2019. Additionally, I interned at the Samsung R&D Institute in 2018.

Experience

7 yrs 6 mos

Total Experience

11 mos

Average Tenure

1 yr 1 mo

Current Experience

Guide labs

Research Engineer

Apr 2025 – Present · 1 yr 1 mo · San Francisco Bay Area · On-site

San diego supercomputer center

AI Research Engineer

Nov 2023 – Apr 2025 · 1 yr 5 mos · San Diego, California, United States · On-site

Uc san diego

7 roles

Graduate Teaching Assistant

Apr 2023 – Jun 2023 · 2 mos · San Diego, California, United States · On-site

DSC 140A - Probabilistic Modeling and Machine Learning

Graduate Teaching Assistant

Jan 2023 – Mar 2023 · 2 mos · San Diego, California, United States · On-site

CSE 166 - Image Processing

Graduate Student Researcher

Promoted

Oct 2022 – Aug 2023 · 10 mos · San Diego, California, United States · On-site

Machine LearningResearchMatplotlibRoboticsDeep Reinforcement LearningDeep Learning+8

Graduate Teaching Assistant

Sep 2022 – Dec 2022 · 3 mos · San Diego, California, United States · On-site

ECE 225A - Probability and Statistics for Data Science

Graduate Student Researcher

Promoted

Apr 2022 – Aug 2022 · 4 mos · San Diego, California, United States · On-site

Worked under the supervision of Prof. Lily Weng on Adversarial Robustness Analysis of Deep Models. Conducted an empirical analysis of the CLIP model's resilience to adversarial perturbations
and devised an attack mechanism to generate adversarial examples. Trained robust classifier with strong provable guarantees against adversarial attacks.

Adversarial AnalysisExplainable AINumPyDeep LearningPython (Programming Language)PyTorch+2

Graduate Teaching Assistant

Mar 2022 – Jun 2022 · 3 mos · San Diego, California, United States · On-site

ECE 109 - Probability and Statistics

Graduate Teaching Assistant

Jan 2022 – Mar 2022 · 2 mos · San Diego, California, United States · On-site

ECE 101 - Linear Signals and Systems

Hitachi

Assistant Researcher

Oct 2019 – Sep 2021 · 1 yr 11 mos · Tokyo, Tokyo, Japan · On-site

Worked in the Intelligent Vision Research Group on a diverse range of AI and computer vision problems such as Visual Localization and Mapping, SLAM, Camera Tracking, Navigation, Object detection and segmentation, Hazardous Activity detection, etc.

Machine LearningSoftware DevelopmentC++DockerGitMatplotlib+11

Indian institute of technology, bombay

2 roles

Teaching Assistant

Jan 2019 – Apr 2019 · 3 mos · Mumbai, Maharashtra, India · On-site

EE 210 - Signals and Systems
Assisted Prof. Jayakrishnan Nair in the evaluation of assignments, exams, conducting office-hours, etc.

Undergraduate Student Researcher

Aug 2018 – Jul 2019 · 11 mos · Mumbai, Maharashtra, India · On-site

Designed a novel control algorithm to drive a multi-agent system to a target destination.
Utilized global iterative solvers to estimate optimal paths in constrained conditions.
Learned to accurately predict pursuer-evader trajectories using an attention-LSTM model.

Machine LearningNumerical SimulationMatplotlibRoboticsPython (Programming Language)MATLAB+2

Samsung r&d institute india - bangalore private limited

Summer Intern

May 2018 – Jul 2018 · 2 mos · Bengaluru, Karnataka, India · On-site

As part of the text recognition team at the Advanced Technology Lab, I played a key role in developing a 3D handwritten text recognition system that estimated wrist and hand movements using Samsung smartwatch IMU sensors.
One of the major challenges was modeling raw sensor noise, causing significant drifts in the generated character patterns. To mitigate this issue, I implemented adaptive frequency filters to preprocess the raw signals and improve the signal-to-noise ratio.
Designed the framework for data collection, and trained a SVM and LSTM model to learn the relation between hand movements and character patterns.
Achieved an impressive 93% text recognition accuracy on unseen data.

Unmesh mashruwala innovation cell

Technical Team Member

Aug 2017 – Apr 2018 · 8 mos · Mumbai, Maharashtra, India · On-site

Worked as part of the Autonomous Driving Car team (SeDriCa) under Innovation Cell, IIT Bombay. Focused on solving problems related to the detection of roads, lanes, obstacles under varying lighting conditions, especially targeted at Indian driving conditions.

Machine LearningMatplotlibStatistical Signal ProcessingDeep LearningPython (Programming Language)Text Recognition+1

Indian institute of technology, bombay

Undergraduate Student Researcher

Apr 2017 – Sep 2017 · 5 mos · Mumbai, Maharashtra, India · On-site

Worked under the supervision of Prof. Subhasis Chaudhuri at VIP Lab, IIT Bombay focusing on Zero-Shot Learning for Object Recognition.
To address this challenge, I proposed and developed a semi-supervised VGG16 autoencoder model, which effectively learned visual-semantic mapping utilizing Word2Vec features.
As a result of my contributions, I successfully enhanced the performance of ZSL's unseen class on the Animals with Attributes dataset from 58.7% to an impressive 65.3%.

Autonomous Driving CarDeep LearningPython (Programming Language)Image ProcessingComputer VisionTensorflow+1