Kousik Rajesh

AI Researcher

San Francisco, California, United States3 yrs 6 mos experience

Most Likely To Switch

Key Highlights

Expert in Machine Learning and Big Data technologies.
Proven track record in developing advanced algorithms.
Strong academic background with top grades in relevant fields.

Stackforce AI infers this person is a Machine Learning Engineer with expertise in SaaS and advanced algorithm development.

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Skills

Core Skills

Applied Machine LearningBig DataFederated LearningMachine LearningDeep LearningStatistical ModelingOptimizationConvolutional Neural Networks (cnn)

Other Skills

AlgorithmsApache SparkAstronomyC (Programming Language)C++Computer ScienceComputer VisionCryptographyData AnalysisData StructuresData VisualizationDjangoGNNGenetic AlgorithmsGenetic Programming

Experience

3 roles

Machine Learning Engineer II

Promoted

Sep 2025 – Present · 6 mos

Working on foundation models for user sequences, scaling transformers, model efficiency and heterogeneous graph representation learning in the Applied Science team under the Advanced Technology Group (ATG).

Apache SparkBig DataFederated LearningGraph Neural NetworksMultimodal MLTranformer Optimization+2

Machine Learning Engineer

Feb 2024 – Sep 2025 · 1 yr 7 mos

Machine Learning Intern

May 2023 – Aug 2023 · 3 mos · San Francisco, California, United States · Hybrid

Worked on heterogeneous graph embeddings for recommender systems at the Applied Science team.
Developed a hierarchical transformer-based edge prediction model for simultaneously learning multi-entity embeddings from a pin, board, and search interaction graph on a 30B node graph.
Improved offline search retrieval metrics by 23%, repin recall by 5% over production searchsage and graphsage respectively, and introduced board embeddings for the first time.

Applied Machine LearningMachine LearningPyTorchGNNTranformer OptimizationMultimodal ML+3

Carnegie mellon university

Graduate Teaching Assistant

Aug 2023 – Mar 2024 · 7 mos · Pittsburgh, Pennsylvania, United States · On-site

Graduate Teaching Assistant for the course 10-719 Federated Learning (Fall 2023) and 10-605 Machine Learning with Large Datasets (Spring 2023) in the Machine Learning Department

Big DataApplied Machine LearningFederated LearningApache SparkPyTorch

D. e. shaw india private limited

Software Developer Intern

May 2021 – Jul 2021 · 2 mos · Hyderabad, Telangana, India

Developed statistical models and outlier filtering techniques to process a dataset with 15 billion data points.
Implemented a parallelized DBSCAN based clustering and automated the hyperparameter discovery process.
Devised a novel BFS based coarse pre-clustering technique for parallelization and reduced inference time by 20x.

Machine LearningStatistical ModelingData AnalysisData VisualizationPython (Programming Language)

Unsw

Research Intern

Jun 2020 – Feb 2021 · 8 mos · Sydney, New South Wales, Australia

Built on existing genetic programming approaches for the Resource Constrained Project Scheduling Problem (RCPSP).
Developed a Multidimensional Archive of Phenotypic Elites (MAP-Elites) based Quality-Diversity algorithm for evolving operator trees to find heuristic solutions to the RCPSP.
Demonstrated the benefits of the proposed hyper-heuristic with respect to both performance and solution diversity.

Machine LearningOptimizationPython (Programming Language)Parallel AlgorithmsGenetic Programming

Indian institute of technology gandhinagar

Research Intern

Apr 2020 – Jun 2020 · 2 mos · India

Surveyed Convolutional Neural Network (CNN) based techniques for generation of High Dynamic Range (HDR) from Low Dynamic Range (LDR) images.
Developed an encoder-decoder based CNN for image-to-image translation and compared it with existing approaches.

PyTorchConvolutional Neural Networks (CNN)Deep Learning