Ayush Garg

Lead ML Engineer

Bengaluru, Karnataka, India9 yrs 8 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in automating customer support using ML.
Proficient in fine-tuning generative language models.
Experienced in building real-time ML solutions.

Stackforce AI infers this person is a Machine Learning Engineer specializing in customer support automation within SaaS.

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Skills

Core Skills

Machine LearningNatural Language Processing (nlp)

Other Skills

Supervised LearningPythonDockerAirflowSparkStochastic Gradient DescentEnsemble ModelsHadoopHiveMatlabAnalyticsJavaSASSQLTeradata

About

As a Machine Learning Engineer at Uber, I use cutting-edge techniques to automate and improve the customer support experience. I fine-tune generative language models for response generation, design evaluation frameworks, and work with discriminative models for emotion recognition, toll refunds, and waiting time prediction.

Experience

9 yrs 8 mos

Total Experience

3 yrs 2 mos

Average Tenure

5 yrs

Current Experience

Uber

Staff Machine Learning Engineer

May 2021 – Present · 5 yrs · Bengaluru, Karnataka, India

I'm a Staff MLE in the customer support engineering team at Uber. We use discriminative and generative ML to automate and better the customer support experience at Uber. My work involves fine-tuning the best Open Source generative LLMs for generating support responses, Retrieval Augmented Generation, designing evaluation framework for Generative models among other things.
Previously, I've worked with discriminative BERT-like LLMs for Emotion Recognition, automating toll refunds, predicting waiting times for customers in support queues etc.

Supervised LearningNatural Language Processing (NLP)Machine LearningPython

Grab

Senior Machine Learning Engineer

Aug 2018 – Apr 2021 · 2 yrs 8 mos · Singapore

End-to-End ML model training and productionization. Served multiple realtime ML models on Docker/as ONNX. Built spark data pipelines on airflow. Trained multiple graph, sequence, ensemble, and anomaly detection models.

Machine LearningDockerAirflowSpark

American express

Decision Scientist

Aug 2016 – Aug 2018 · 2 yrs · Gurugram, Haryana, India

Experimentation on Online Learning models using Stochastic Gradient Descent. Trained Ensemble Models for Response Rate prediction, Default probability prediction etc.

Machine LearningStochastic Gradient DescentEnsemble Models