Abhishek Maiti

AI Researcher

Abu Dhabi, Abu Dhabi Emirate, United Arab Emirates6 yrs 11 mos experience

Most Likely To Switch

Key Highlights

Expert in training large multilingual ML models.
Strong background in machine learning and computer vision.
Proven track record in cross-functional collaborations.

Stackforce AI infers this person is a Machine Learning Engineer specializing in Computer Vision and Natural Language Processing.

Contact

Skills

Core Skills

Machine LearningNatural Language Processing (nlp)Computer Vision

Other Skills

Deep LearningReinforcement LearningModel EvaluationPyTorchPythonImage SegmentationTensorFlowCross-functional CollaborationsGenerative ArtStatisticsWeb DevelopmentJavaTable Tennis

About

Part of the Jais Team (Multilingual LLMs and LVMs) working on machine learning algorithms for training large ML models. I also maintain workatafrontierlab.com You can find out more about my past work and projects at abhishekmaiti.com

Experience

6 yrs 11 mos

Total Experience

1 yr

Average Tenure

1 yr 1 mo

Current Experience

Cerebras systems

Member of Technical Staff - Applied ML

Apr 2025 – Present · 1 yr 1 mo · Abu Dhabi · Hybrid

Part of customer engineering team (also known as forward deployed researcher/engineer). Working on pre and post-training of 8B, 70B and 100B+ multilingual Jais series of models. Leading RL and evaluations. Making sure our customers can say they got the best models in town.

Machine LearningNatural Language Processing (NLP)Deep LearningReinforcement LearningModel Evaluation

Earnin

Senior Machine Learning Engineer

Mar 2024 – Apr 2025 · 1 yr 1 mo · Bengaluru, Karnataka, India · Hybrid

1st IC at Bangalore site.

Deep LearningPyTorchPythonNatural Language Processing (NLP)Machine Learning

Applied Research Engineer

Feb 2022 – Mar 2024 · 2 yrs 1 mo · Bangalore Urban, Karnataka, India · Remote

Working with Trust AI to engineer advanced image and video analysis solutions, ensuring LinkedIn remains compliant with platform policies.

Machine LearningImage SegmentationPyTorchDeep LearningTensorFlowNatural Language Processing (NLP)+2

Wadhwani ai

Associate Machine Learning Scientist - I

Jun 2020 – Apr 2022 · 1 yr 10 mos · Mumbai, Maharashtra, India

Working on 3D generative modelling and disentanglement.
Working on generating synthetic data and reducing the domain gap between multiple streams of data.
working on self supervised learning algorithms for weight estimation

Image SegmentationPyTorchComputer VisionCross-functional CollaborationsMachine Learning

Indraprastha institute of information technology, delhi

2 roles

Teaching Assistant

Aug 2019 – Nov 2019 · 3 mos · New Delhi

Teaching assistant for CSE343 (Machine Learning) offered to 3rd year undergraduates across disciplines. Duties involve grading, conducting tutorials holding office hours for doubts.

Computer Vision

Teaching Assistant

Jan 2019 – May 2019 · 4 mos · New Delhi Area, India

Teaching Assistant for Data Structures & Algorithm Course offered to the 1st year undergraduates.

Expedia group

Associate Software Developer Intern

May 2019 – Jul 2019 · 2 mos · Gurgaon, India

Working with the Egencia Car Team

Laboratory for computational social systems, iiit-delhi

Research Intern

Aug 2018 – Nov 2018 · 3 mos · New Delhi Area, India

Quantified impact for scientific texts using Citation Dispersion Trees
(CDT) and theorized bounds and nodes for inflicting adversarial
changes. Published at ACM/IEEE Joint Conference On Digital Libraries (JCDL 2019, A Core A* Conference) and awarded the best student paper prize.

Computer Vision

Ibm

Summer Research Intern

Apr 2018 – May 2018 · 1 mo · New Delhi Area, India

Studying the evolution of technological concepts and their temporal relationship with each other using deep learning and Natural Language Processing.

Indraprastha institute of information technology, delhi

Research Intern

Aug 2017 – Jan 2018 · 5 mos · New Delhi Area, India

Engaged in designing and simulating prediction algorithms for damage done by security vulnerabilities and attacks originating from malicious legacy codes.
Running models such as SVMs on datasets such as CVE and OSVDB for predicting exploits and their patches.