Rajas Bansal

AI Researcher

San Francisco, California, United States6 yrs 3 mos experience

Most Likely To Switch

Key Highlights

Expert in Machine Learning and Graph Neural Networks.
Experience in developing scalable training methods.
Strong academic background from Stanford and IIT Delhi.

Stackforce AI infers this person is a Machine Learning Engineer with a focus on SaaS and research applications.

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Skills

Core Skills

Machine Learning

Other Skills

Graph Neural NetworksSamplingInfluence MetricRecommender SystemsBackward Compatible EmbeddingsNatural Language Processing (NLP)JavaAlgorithmsData StructuresDistributed SystemsPython (Programming Language)C++Reinforcement LearningParallel Programming

Experience

6 yrs 3 mos

Total Experience

1 yr 2 mos

Average Tenure

1 yr 4 mos

Current Experience

Together ai

Machine Learning Engineer

Jan 2025 – Present · 1 yr 4 mos · San Francisco, California, United States

Refuel

Founding Machine Learning Engineer

Jan 2023 – Jan 2025 · 2 yrs · San Francisco Bay Area · Hybrid

Acquired by Together.ai: https://www.together.ai/blog/together-ai-acquires-refuel-ai

Machine Learning

Amazon

Applied Science Intern

Jun 2022 – Sep 2022 · 3 mos · Palo Alto, California, United States

Developed scalable training methods to train Graph Neural Networks on a billion
node real world graph.
Used sampling to reduce the size of the input graph.
Introduced a novel influence metric to pick the important nodes in the graph. Sampling 5% of graph preserves 98% of accuracy, reducing memory and compute.

Graph Neural NetworksSamplingInfluence MetricMachine Learning

Stanford university

Research Assistant

Sep 2021 – Sep 2022 · 1 yr · Stanford, California, United States

Working as a Research Assistant at the SNAP lab with Prof. Jure Leskovec on recommender systems and graph neural networks. Worked on developing backward compatible embeddings useful in industry settings where the emedding model may be updated frequently. Work published in KDD 2022.

Recommender SystemsGraph Neural NetworksBackward Compatible EmbeddingsMachine Learning

Cohesity

Research Engineer

Aug 2020 – Sep 2021 · 1 yr 1 mo

Indian institute of technology, delhi

2 roles

Undergraduate Teaching Assistant

Jan 2020 – May 2020 · 4 mos

Teaching assistant for the course : Introduction to Computer Science

Undergraduate Teaching Assistant

Jul 2019 – Dec 2019 · 5 mos

Teaching assistant for the course : Data Structures and Algorithms.

Aces-acm, iit delhi

Secretary, ACES-ACM IIT Delhi

Jul 2019 – May 2020 · 10 mos · Greater Delhi Area

Tower research capital

Summer Intern

May 2019 – Jul 2019 · 2 mos · Gurugram, Haryana, India

Worked with the trading team Northmoore

National university of singapore

Research Intern

May 2018 – Jul 2018 · 2 mos · Singapore

Implemented Validation Buffer, an out-of-order retirement microarchitecture, committing instructions without checkpointing, providing higher performance and lower resource contention. Showed improvement on the SPEC-Int and FP benchmarks. Built the processor in Chisel language over the RISC-V ISA open source microarchitecture BOOM, developed at Berkeley. Implemented an OoO commit structure and mechanism along with an aggressive register reclamation algorithm.