Aditi Dekhane

CEO

Mumbai, Maharashtra, India7 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in AI-driven automation and NLP solutions.
Proven track record in speech recognition model development.
Strong experience in cross-regional client engagement.

Stackforce AI infers this person is a skilled AI and automation specialist with a focus on speech technology and NLP.

Contact

Skills

Core Skills

NlpAutomationSpeech RecognitionDeep LearningSpeech TechnologyMachine Learning

Other Skills

Client Requirement AnalysisData ProcessingTensorFlowPyTorchSelf-Supervised LearningMultilingual DatasetsFew-shot LearningDatabase IntegrationSpeech ProcessingPL/SQLStatistical Data AnalysisBig DataGenerative AIHTMLBootstrap (Framework)

About

Blending research mindset with builder energy, I enjoy working at the intersection of AI, business impact, and automation where models stop being slides and start becoming products. I like taking ideas from “this could work” to “this is live” My experience spans speech recognition on edge devices at Samsung R&D, few-shot multilingual ASR research at IIIT Bangalore, and a deep learning–based billing recommender deployed on a real platform. Along the way, I’ve also led programming for an AIR 3 Robocon team, building perception and decision-making pipelines for autonomous robots that have to work under real-world constraints, not just benchmarks. I’m excited about roles where intelligent automation can unlock new revenue, efficiency, or user experiences and where there’s room to experiment fast, ship reliably, and keep learning.🚀

Experience

7 mos

Total Experience

5 mos

Average Tenure

2 mos

Current Experience

Expertrons

CRO Specialist

Mar 2026 – Present · 2 mos · Mumbai

The konsol

2 roles

AI Marketing Associate

Oct 2025 – Dec 2025 · 2 mos

Led end-to-end client requirement analysis and delivery for cross-regional clients (Germany & USA), ensuring campaign alignment, timely execution, and converted 50+ prospects into leads.
Engineered and deployed scalable browser-automation pipelines, reducing 150+ hours of manual data processing and enhancing operational efficiency and reliability.
Designed and integrated NLP-driven AI variable personalization modules, improving workflow accuracy and boosting outbound performance by up to 80%

NLPAutomationClient Requirement AnalysisData Processing

AIE- Outreach Automation Intern

Jul 2025 – Sep 2025 · 2 mos

Samsung r&d institute india - bangalore

Machine Learning Engineer - Audio/Speech

Aug 2024 – Oct 2024 · 2 mos

Developed and fine-tuned speech recognition models using TensorFlow and PyTorch, leveraging self-supervised learning to improve accuracy.
Preprocessed large-scale multilingual audio datasets using techniques like MFCC and spectrogram analysis to enhance model training.
Collaborated with cross-functional teams to integrate real-time speech models into mobile and IoT devices, optimized using ONNX and TensorRT.
Conducted performance tuning and inference optimization with GPU acceleration, reducing model inference time and increasing computational efficiency.

TensorFlowPyTorchSpeech RecognitionSelf-Supervised LearningMultilingual DatasetsDeep Learning

International institute of information technology bangalore

Summer Research Intern

May 2024 – Jul 2024 · 2 mos · Bengaluru, Karnataka, India

Foundation-Model design based on Few-shot Learning (Multi-lingual Speech Technology Project)
This project involves building components for the design of
Foundation Models for End-to-End Automatic Speech Recognition
(E2E ASR) based on Few-shot Learning, set in Self-Supervised Learning frameworks. •Specifically, it will be proposing and
experimenting with new methods within the paradigm of Matching-
Networks (MN), a Meta-/Metric-Learning based Few-Shot Learning
algorithm, to come up with Foundation Models, completely derived
from Unsupervised Data. •This is in contrast to the original MN algorithm which is essentially a Supervised FSL paradigm.

Few-shot LearningSpeech Technology

Sarathi softech pvt ltd

Machine Learning Intern

Jan 2024 – Jun 2024 · 5 mos · Pune, Maharashtra, India

Worked on integration of ML with their Database systems for automatic data updtaion and analysis.
Deployed a DL based intelligence system to recommend users the best possible usage plan.

Machine LearningDatabase Integration