I am a Machine Learning Engineer with expertise in computer vision, deep learning, and cloud AI solutions. I have extensive experience optimizing image-to-image translation, defect detection, and machine learning architectures, driving accuracy and efficiency gains. I am proficient in Python, TensorFlow, PyTorch, NVIDIA TensorRT, Azure, and Google Cloud Platform, enabling scalable AI deployment. I am passionate about leveraging cutting-edge machine learning techniques to develop high-performance models and streamline system workflows.

Digvijay Yadav

I am a Machine Learning Engineer with expertise in computer vision, deep learning, and cloud AI solutions. I have extensive experience optimizing image-to-image translation, defect detection, and machine learning architectures, driving accuracy and efficiency gains. I am proficient in Python, TensorFlow, PyTorch, NVIDIA TensorRT, Azure, and Google Cloud Platform, enabling scalable AI deployment. I am passionate about leveraging cutting-edge machine learning techniques to develop high-performance models and streamline system workflows.

Available to hire

I am a Machine Learning Engineer with expertise in computer vision, deep learning, and cloud AI solutions. I have extensive experience optimizing image-to-image translation, defect detection, and machine learning architectures, driving accuracy and efficiency gains.

I am proficient in Python, TensorFlow, PyTorch, NVIDIA TensorRT, Azure, and Google Cloud Platform, enabling scalable AI deployment. I am passionate about leveraging cutting-edge machine learning techniques to develop high-performance models and streamline system workflows.

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Experience Level

Expert
Expert
Expert
Expert
Expert

Work Experience

Senior Machine Learning Engineer at SCSI Connect LLC
January 31, 2025 - August 3, 2025
Designed and implemented image-to-image translation algorithms using Patch-GAN on whole-slide histology images, significantly enhancing biomarker detection accuracy by 40%. Leveraged Google Cloud Platform (GCP) and Python for scalable and efficient data processing, ensuring high-performance model execution. Optimized machine learning training pipelines by integrating PyTorch mixed-precision functionality, reducing training time per epoch from 12 to 5 minutes, enabling faster iteration and improved performance for detecting multiple biomarkers. Spearheaded modularization and restructuring of the existing codebase implementing best coding practices, resulting in a 70% reduction in system crashes caused by memory overload. Accelerated model inferencing times for biomarker detection by employing parallel computing techniques, cutting processing time from 20 to 5 minutes.
Data Scientist Intern at Schaeffler Group
September 30, 2023 - August 3, 2025
Designed and implemented KPI metrics focused on category-level precision and recall, collaborating closely with product teams to improve communication with non-technical stakeholders, resulting in a 35% increase in business profitability. Developed advanced computer vision models using Faster-RCNN and Single-Shot Detector (SSD) architectures, increasing defect detection accuracy by 40%. Optimized model efficiency leveraging Python and TensorFlow for high-speed and reliable defect identification in manufacturing. Engineered scalable supervised data processing pipelines using Azure and Python, enhancing large-scale defect detection accuracy by 30% and reducing annual operational expenses by $5,000. Leveraged cloud computing and machine learning techniques to streamline data workflows and improve system performance.
Computer Vision Engineer at Visionify.ai
August 31, 2022 - August 3, 2025
Optimized deep learning models using NVIDIA TensorRT for MobileNet-V2-based architectures, increasing brick defect detection accuracy in video streams from 85% to 90%. Streamlined application lifecycle management on Microsoft Azure using Agile methodologies and Jira, improving model efficiency by 30% and driving higher business productivity. Designed and implemented instance segmentation-based unsupervised learning models for object detection in TORO irrigation pipes using Python, OpenCV, and custom deep learning architectures, significantly enhancing detection accuracy and real-time processing capabilities.
Senior Machine Learning Engineer at CSI Connect LLC
January 31, 2025 - August 24, 2025
Designed and implemented image-to-image translation algorithms using Patch-GAN on whole-slide histology images, significantly improving biomarker detection accuracy by 40%. Leveraged Google Cloud Platform and Python for scalable and efficient data processing, ensuring high-performance model execution. Optimized machine learning training pipelines by integrating PyTorch mixed-precision functionality, reducing training time from 12 minutes to 5 minutes per epoch. Spearheaded modularization and restructuring of codebase implementing best coding practices, resulting in a 70% reduction in memory-overload crashes and ensuring stable model deployment. Accelerated model inferencing times for biomarker detection by employing parallel computing techniques, cutting down processing time from 20 minutes to 5 minutes.
Data Scientist Intern at Schaeffler Group
September 30, 2023 - August 24, 2025
Designed and implemented KPI metrics focused on category-level precision and recall, collaborating closely with product team to improve communication with non-technical stakeholders, increasing business profitability by 35%. Developed advanced computer vision models using Faster-RCNN and Single-Shot Detector architectures, increasing defect detection accuracy by 40%. Optimized model efficiency leveraging Python and TensorFlow, ensuring high-speed and reliable defect identification in manufacturing processes. Engineered scalable supervised data processing pipelines using Azure and Python, enhancing large-scale defect detection accuracy by 30% and reducing annual operational expenses by $5,000. Leveraged cloud computing and machine learning techniques to streamline data workflows and improve system performance.
Computer Vision Engineer at Visionify.ai
August 31, 2022 - August 24, 2025
Optimized deep learning models using NVIDIA TensorRT for MobileNet-V2-based architectures, increasing brick defect detection accuracy in video streams from 85% to 90%. Achieved performance improvements through model optimization and advanced computer vision techniques. Streamlined application lifecycle management on Microsoft Azure by leveraging Agile methodologies and Jira, improving model efficiency by 30% and boosting business productivity via structured workflows and automation. Designed and implemented instance segmentation-based unsupervised learning models for object detection in TORO irrigation pipes, leveraging Python, OpenCV, and custom deep learning architectures, significantly enhancing detection accuracy and real-time processing capabilities.

Education

Health Data Science at Dartmouth College
August 1, 2022 - June 30, 2024
Health Data Science at Dartmouth College
August 1, 2022 - June 30, 2024

Qualifications

Add your qualifications or awards here.

Industry Experience

Healthcare, Manufacturing, Life Sciences, Computers & Electronics, Software & Internet