Open to opportunities

Anuj Kumar

@anujkumar4

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Senior ML Engineer specializing in computer vision and machine learning.

Canada

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What I'm looking for

I am looking for a role that fosters innovation and collaboration, where I can leverage my machine learning expertise to solve complex problems and contribute to impactful projects.

I am a Senior ML Engineer with a strong foundation in machine learning and computer vision, currently working at Intellifai in Canada. My journey began with a BTech from IIT Delhi, where I developed an AI-driven talking head avatar system that significantly reduced video production time by 50%, enhancing virtual communication for over 10,000 users. My academic background is complemented by hands-on experience in developing advanced models, including an InpaintAnything model that utilizes text to remove objects from images.

In my previous role at DentalAI, I co-founded a team that managed data curation for a robust end-to-end model pipeline, ensuring compliance with HIPAA standards. My contributions included training a Transformer model on a massive dataset, achieving a remarkable 93.1% F1 score in a 3D point cloud completion task. I thrive in collaborative environments, having successfully led teams to develop innovative solutions that leverage the latest advancements in machine learning.

Experience

Work history, roles, and key accomplishments

Current

Sr. ML Engineer

Current

Intellifai

Mar 2024 - Present (1 year 2 months)

Developed an AI-driven talking head avatar system for seamless lip-syncing, reducing video production time by 50% and enhancing virtual communication quality for over 10,000 users. Developed an Inpaint Anything model with 34 PSNR which uses text to remove an object in an image using Diffusion and Grounding DINO model. Collaborated with data team to test 200+ videos to check robustness of the model

AI Machine Learning Lip Sync Diffusion Models Video Production Data Testing

Cofounding Team Member

DentalAI

Mar 2023 - Feb 2024 (11 months)

Managed data team to ensure 6000 data curation applying MLOPS and contributing to a robust end-to-end model pipeline incorporating HIPAA compliance for real-world deployment. Successfully managed website team to develop a website to let users visualize 3D models and perform end to end prediction. Successfully trained a Transformer model on a massive 15GB point cloud dataset, achieving 93.1% F1 sco

MLOps HIPAA 3D Modeling Google Cloud Platform

Computer Vision Engineer

SpyneAI

Nov 2022 - Feb 2023 (3 months)

Developed a personalized image-to-image translation model for a car catalogue using the Dreambooth Stable Diffusion model, resulting in studio-like images. Employed prompt engineering techniques like prompt matrix in InstructPix2Pix and ControlNet Stable Diffusion models to get 25000 studio like car images. Created a real-time object detection model on edge using YoloV7, trained on 80000 images ac

YOLOv7 Image To Image Translation Dreambooth Stable Diffusion Prompt Engineering InstructPix2Pix ControlNet Object Detection YoloV7

Computer Vision Intern

Sony

May 2022 - Oct 2022 (5 months)

Contributed to open source nnabla-a deep learning framework. Enhanced the efficiency of using Explainable AI by 90% by developing XAI API. Reduced data visualization of XAI application in CNN by 80% by modifying Saliency, SHAP and Integrated Gradients explanation methods. Improved the accuracy of Resnet, Resnext, WideResnet, and Densenet by 20% by integrating it with Attention Branch Networks.

Explainable AI CNN SHAP Integrated Gradients Attention Branch Networks

Machine Learning Researcher

Purdue University

Sep 2021 - Oct 2021 (1 month)

Built a computer vision model that can predict vital signs with 89.22% F1 score using face detection and signal processing methods.

Computer Vision Signal Processing Machine Learning

Deep Learning Researcher

University of California

Feb 2021 - Aug 2021 (6 months)

Trained 3D CNN and LSTM on 400+ videos on colorectal surgery and enhanced the accuracy of surgical phase recognition to 84.66%.

Surgical Phase Recognition Deep Learning

Education

Degrees, certifications, and relevant coursework

Indian Institute of Technology Delhi

Bachelor of Technology, Computer Science

Grade: 3.0 / 4.0

Completed a Bachelor of Technology degree focusing on core computer science principles. Gained foundational knowledge in programming, data structures, and algorithms, preparing for advanced roles in technology.

Chinmaya Vidyalaya

Senior Secondary Certificate, Science (PCMB)

Grade: 90.8%

Completed secondary education with a focus on Physics, Chemistry, Mathematics, and Biology (PCMB). Achieved strong academic performance, laying a solid foundation for higher studies.