Karthik Kandukuri

AI Researcher

Bengaluru, Karnataka, India6 yrs 7 mos experience

Highly Stable

Key Highlights

Expert in building high-performance AI models.
Proficient in deep learning and recommendation systems.
Strong background in competitive coding.

Stackforce AI infers this person is a Fintech AI Engineer specializing in machine learning and recommendation systems.

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Skills

Core Skills

Deep LearningRecommendationMachine LearningNlpRisk Modelling

Other Skills

C (Programming Language)CplexData StructuresKerasPython (Programming Language)PytorchTensorFlow

About

Machine Learning Enthusiast with experience in building large scale, high performance AI models. I am currently building AI systems related to Recommendation engine domain. Apart from these, I continue to invest my free time in competitive coding. Core Competencies: Machine Learning, Deep Learning, Artificial Intelligence, Recommendation, Risk Modelling, Optimization.

Experience

Enphase energy

AI/ML Staff Engineer

May 2023 – Present · 2 yrs 10 mos · Bengaluru, Karnataka, India · Hybrid

Mastercard ai garage

3 roles

AI Engineer III

Oct 2022 – May 2023 · 7 mos

◦ Complete ownership of a Smart Product Recommendation - Drive Thru project. Built a state of the art DL based optimized revenue focused recommendation engine using Deep Factorization
Machine.

Deep LearningRecommendation

AI Engineer II

Apr 2021 – Sep 2022 · 1 yr 5 mos

◦ Worked on Mastercard Interface Processor (MIP) Server failure detection. Built a NLP based semi-supervised solution that learns the complex understanding of healthy and failure log
patterns using an ensemble of DL based sequential LSTM autoencoder and multivariate Gaussian distribution.
◦ Technologies and Tools: Pytorch, Keras, TensorFlow

PytorchKerasTensorFlowMachine LearningNLP

AI Engineer

Jun 2019 – Mar 2021 · 1 yr 9 mos

Worked as a ML Engineer in the Artificial Intelligence team.
◦ Risk Modelling use-cases.
◦ Built an optimization solution on Business-to-Business high level invoice payments, which recommends the optimal channel and timing to pay in order to maximize the buyer savings based on supplier preferences.
◦ Technologies and Tools: Pytorch, Keras, TensorFlow, Cplex

PytorchKerasTensorFlowCplexMachine LearningRisk Modelling