Arvind Yadav

Lead ML Engineer

Delhi, India7 yrs 4 mos experience

AI EnabledAI ML Practitioner

Key Highlights

8+ years of experience in AI and ML systems.
Led successful AI initiatives at Siemens Energy.
Founded GakudoAI, driving innovation in K-12 education.

Stackforce AI infers this person is a Machine Learning Engineer specializing in AI systems for industrial and educational applications.

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Skills

Core Skills

Machine LearningComputer VisionGenerative AiNatural Language Processing (nlp)Data Science

Other Skills

Machine Learning AlgorithmsCloud ComputingArtificial Intelligence (AI)Model DevelopmentDocker ProductsConvolutional Neural Networks (CNN)Fine TuningMLOpsPattern RecognitionLLaMAVector DatabasesObject-Oriented Programming (OOP)Continuous Integration and Continuous Delivery (CI/CD)Image AnalysisModeling

About

Lead Machine Learning Engineer with 8+ years of experience designing, scaling, and owning production-grade AI systems end to end across Computer Vision, Generative AI, and applied ML in both startups and global enterprises. Currently leading machine learning initiatives at Siemens Energy, with ownership of industrial-scale vision systems spanning model architecture, data strategy, deployment, and optimization—focused on robustness, generalization across operating conditions and low-latency inference in production environments. Previously founded and built GakudoAI, where I led the development of a multi-agent GenAI platform for K–12 assessment and career guidance, taking the product from initial concept to production deployment, early user adoption and startup ecosystem validation. I bring a strong track record of technical leadership, mentoring teams, and translating ambiguous business and domain problems into reliable, deployable ML solutions—driving measurable impact through accuracy improvements, inference optimization and operational efficiency. IIT Delhi graduate, motivated by solving real-world problems through applied AI and building ML systems that operate reliably at scale. Particularly interested in high-impact problems at the intersection of GenAI, computer vision and large-scale ML systems.

Experience

7 yrs 4 mos

Total Experience

1 yr 1 mo

Average Tenure

9 mos

Current Experience

Siemens energy

Lead ML Engineer

Sep 2025 – Present · 9 mos

Working on production-grade computer vision and machine learning systems for industrial-scale energy applications, with end-to-end ownership from model design to deployment and optimization.
Focus areas include robust vision model architecture, data-agnostic generalisation and low-latency inference at scale.

Machine Learning AlgorithmsComputer VisionCloud ComputingArtificial Intelligence (AI)Machine Learning

Gakudoai

Founder & Lead AI Engineer

Jul 2024 – Sep 2025 · 1 yr 2 mos · Delhi, India · Remote

Led end-to-end development of a multi-agent AI system delivering personalized K-12 assessment insights and career recommendations, from model design to production deployment.

Natural Language Processing (NLP)Model DevelopmentMachine LearningDocker ProductsGenerative AI

Walker digital table systems, llc

Senior Machine Learning Engineer

May 2023 – Jul 2024 · 1 yr 2 mos · Gurugram, Haryana, India

🔹 Blackjack with Computer Vision:
Led a 4-member ML team to design and deploy real-time object tracking systems for casino games, boosting detection and classification accuracy from 72% to 98%.
Developed and implemented robust computer vision pipelines for player card detection and classification, optimized for diverse lighting and environmental conditions.
Designed a custom object tracking algorithm capable of handling occlusions and dynamic camera angles across various casino table game setups.
🔹 LLM-Based Query Answering System:
Built and deployed a production-grade, LLM-powered Q&A system for internal product documentation.
Utilized LLaMA 2 for text generation and Pinecone for high-speed vector search, achieving a 95% retrieval recall.
Evaluated the experiments using Factual Correctness metrics and Answer Relevancy, achieved an overall avg correctness of 89%.
The system reduced documentation-related support tickets by 15%, improving internal team efficiency and product usability.

Convolutional Neural Networks (CNN)Fine TuningMachine Learning AlgorithmsMLOpsComputer VisionMachine Learning

Stats perform

Machine Learning Engineer

Oct 2022 – May 2023 · 7 mos

🔹 Teamid Classification: Experimented with different CNN models. Selected & fine-tuned CNN-based model to get feature-vector & converted to 5-class output for soccer players. Achieved 92.3% accuracy on 50 clips video test dataset
🔹 Soccer Pitch Shadow Segmentation: Built semantic-segmentation model using U-net architecture & mobileNetV2 as backbone & achieved 94.7% IOU
🔹 Image Generation: Jersey colour transfer using GAN-based DGNet Model on soccer player crop data and achieved 18.2 FID Score on test dataset(25k tracks)

Object-Oriented Programming (OOP)Machine Learning AlgorithmsContinuous Integration and Continuous Delivery (CI/CD)Computer VisionMachine Learning

Exl

Senior Data Scientist

Sep 2021 – Oct 2022 · 1 yr 1 mo · Gurugram, Haryana, India

🔹 Helped EdTech client in improving the performance of email and SMS campaigns by suggesting best time slots for the campaigns. Open Rate improved by 23% and CTR improved by 18%
🔹 Worked with a US based sports league, handled end-to-end data-preparation, building & deployment ML Model to create FAN Segments and achieved 87% Accuracy

Natural Language Processing (NLP)Machine Learning AlgorithmsMLOpsData ScienceMachine Learning

Decimal technologies

Data Scientist

Nov 2020 – Sep 2021 · 10 mos · Gurugram, Haryana, India

🔹 Signature & POI documents identification and verification model with FasterRCNN & MobileNet
🔹 Recaptured Image Detector with ANN & MobileNet
🔹 Indian bank cheque OCR
🔹 CRUD python APIs with postgreSQL database for user management module

Natural Language Processing (NLP)Machine Learning AlgorithmsComputer VisionData ScienceMachine Learning

Mathlogic

Data Analyst

Feb 2019 – Nov 2020 · 1 yr 9 mos · Gurugram

🔹 Iron Ore detection from Satellite Images using U-Net(ResNet & MobileNet backbone) Architecture
🔹 Scenario planning and workforce & cost optimisation model
🔹 Artificial Neural Network and XGBoost Ensemble
🔹 Loan Approving Model for SMEs for an Indian Finance Company
🔹 Modelling for score prediction for an MNC Credit Bureau Company
🔹 Unsecured Lending Acquisition Modeling for an US Based Lending Company
🔹 ML Trainings: worked as assistant trainer for delivering training in SPARK & Python for corporate clients

ModelingNatural Language Processing (NLP)Machine Learning AlgorithmsData ScienceMachine Learning