Mohd Anas Khan

Machine Learning Engineer

Bengaluru, Karnataka, India7 yrs 3 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in Machine Learning and AI problem-solving.
Proven experience in developing end-to-end ML pipelines.
Strong background in NLP and Computer Vision applications.

Stackforce AI infers this person is a Machine Learning Engineer with expertise in healthcare and travel industries.

Contact

Skills

Core Skills

Large Language Models (llm)Machine LearningComputer VisionData ScienceNatural Language ProcessingDeep Learning

Other Skills

Amazon Web ServicesApplied Machine LearningApplied MathematicsArtificial Intelligence (AI)CC++ClassificationConcept ExtractionContinuous Integration and Continuous Delivery (CI/CD)Convolution Neural Network (CNN)Data ProcessingDataset developmentDependency parsingEnd-to-end pipelineExtraction

About

Anas is a Senior Machine Learning Engineer, currently working at athenahealth. He is highly interested in solving Artificial Intelligence problems using Machine Learning, Computer Vision and Natural Language Processing tools.

Experience

7 yrs 3 mos

Total Experience

1 yr 11 mos

Average Tenure

1 yr 6 mos

Current Experience

Expedia group

Machine Learning Engineer

Dec 2024 – Present · 1 yr 6 mos · India

Working in Search and Ranking Team!

Athenahealth

2 roles

Machine Learning Engineer III

Dec 2023 – Dec 2024 · 1 yr

Worked on Transformers, Large Language Models(LLMs) and model deployments.

TransformersLarge Language Models (LLMs)Model deploymentsLarge Language Models (LLM)Machine Learning

Machine Learning Engineer II

Jul 2021 – Dec 2023 · 2 yrs 5 mos

Working on creating an end-to-end pipeline for labeling and classification of different types of documents from BPO agents. Worked from Extraction, preprocessing, and training to Inference for different pipelines in production.

End-to-end pipelineLabelingClassificationExtractionPreprocessingTraining+3

Zs

Data Science Associate

Aug 2019 – Jul 2021 · 1 yr 11 mos · Greater Bengaluru Area · Hybrid

●Worked on creating a service that can understand the conversation of 2 people using Semantic Analysis. Topic Identification(triggers, emotions), Concept Extraction, Dependency parsing, etc.
●Worked on Flight Booking Recommendations for a Big Airlines Client for multiple use cases, like Overbooking, Spillage, and Spoilage.
● Worked on Patient Switch prediction using multiple techniques like Positive Unlabeled Learning, Classification, Regression, etc.

Semantic AnalysisTopic IdentificationConcept ExtractionDependency parsingFlight Booking RecommendationsPatient Switch prediction+2

Hp

Data Scientist Intern

Jan 2019 – Jun 2019 · 5 mos · Bengaluru, Karnataka, India

Worked on parsing order receipts and bills using diﬀerent text parsers. NLP and computer vision. Also worked on Fraud detection of duplicates bills using computer vision techniques

Text parsingNLPComputer VisionFraud detectionNatural Language Processing

The university of winnipeg

MITACS Globalink Research Intern

May 2018 – Jul 2018 · 2 mos · Manitoba, Canada

♦A comprehensive review of the literature was done to determine the best approaches to training data set development as well as the best categories to use for labeled.
♦Dataset was developed to represent urban structural types using optical remote sensing data (Sentinel-2)that is freely available and labeled using land use planning and census data. Dataset is created using Sentinal 2 for Argentina and Kenya cities using ArcGIS.
♦A model was developed using the Convolution Neural Network(CNN) from scratch to predict slums in the cities.
♦ Due to the highly imbalanced dataset, used the oversampling technique.
♦ Computed per class accuracy and used confusion matrix, F1-score to evaluate the result.
Lab: GeoLead lab(Envi Lab)
Guide: Prof. Christopher Storie

Literature reviewDataset developmentOptical remote sensingConvolution Neural Network (CNN)Oversampling techniqueDeep Learning+1