Aman Kumar

AI Researcher

Singapore, Singapore4 yrs 11 mos experience

Key Highlights

Expert in building scalable AI infrastructure.
Proficient in diverse ML algorithms and frameworks.
Strong experience in deploying ML solutions on Kubernetes.

Stackforce AI infers this person is a Machine Learning Engineer specializing in scalable AI infrastructure and data-driven solutions.

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Skills

Core Skills

Machine LearningComputer VisionData AnalysisData Engineering

Other Skills

APIsAWS LambdaAlgorithmsAmazon Web Services (AWS)Apache CassandraApache KafkaApache SparkApplication Programming InterfacesArgoArtificial Neural NetworksAssistant TeachingBatch ProcessingCassandraConvolutional Neural Networks (CNN)Data Science

About

AWS Certified Solutions Architect & Developer Associate with 4+ years of experience in Data Science, Machine Learning, and ML Infrastructure. Currently a Machine Learning Engineer at Grab, working on building scalable and reliable AI infrastructure to power machine learning systems at scale. Experienced in designing, developing, and deploying complex ML models and solutions using Python and big data technologies such as PySpark and Spark. Proficient with a wide range of machine learning and deep learning algorithms including Random Forest, XGBoost, LightGBM, ANN, CNN, and LSTM. Skilled in exploratory data analysis, statistical modeling, and transforming raw data into actionable insights. Comfortable working across Linux and Windows environments, with a strong ability to identify opportunities and implement solutions that blend cutting-edge research with scalable, production-ready technology. Passionate about enabling AI teams through robust ML infrastructure and MLOps practices.

Experience

4 yrs 11 mos

Total Experience

1 yr 11 mos

Average Tenure

1 yr

Current Experience

Grab

Machine Learning Engineer

May 2025 – Present · 1 yr · Singapore · On-site

Ray based Distributed Training for Hydranet Karta Dash Cam
Scaling multi-task computer vision system for autonomous driving using distributed computing.
Building Ray-based training pipeline that trains single neural network for multiple computer vision tasks (object detection, classification, depth estimation). Enhancing parallel preprocessing actors, task stream management, and unified dataset routing for better performance at scale.
QWEN Batch Inference
Created a scalable, distributed pipeline for Qwen batch labelling. The objective was to process a massive dataset(billions) of images using a large Vision Language Model like QWEN-VL to generate structured labels for traffic signs.

RayDistributed TrainingComputer VisionPythonMachine Learning

Contevolve

2 roles

Senior Data Scientist

Promoted

Apr 2024 – Apr 2025 · 1 yr · Noida, Uttar Pradesh, India

Data Scientist

Apr 2023 – Apr 2024 · 1 yr · Noida, Uttar Pradesh, India

1) Day to day responsibilities include writing complex Python code for application, integrating Oracle with Python, analysis of data, creating prediction ml models for various entities.
2) Creating complex APIs for company's daily data processing.
3) Built an independent python multithreaded application running 24*7 as a service to calculate RealTime bus Arrival and Departure Times, Mileage, Headway and KPIs like Punctuality and Excess Wait Time for a city public bus transport network.
4) Built a forecasting system to predict the number of boardings and alightings at all stops across all routes of a bus network.

PythonOracleAPIsMachine LearningData Analysis

Trapeze group

Software Development Engineer

Apr 2021 – Mar 2023 · 1 yr 11 mos · Switzerland · Hybrid

1.) Building complex Machine Learning models using latest Machine Learning algorithms like Random Forest, XGBoost, Light GBM, H2O, Neural Networks etc
2.) Creating complex APIs for company's daily data processing
3.) Handling tremendous amount of data in Apache Cassandra
4.) Building end to end Machine Learning pipeline and deploying on Kubernetes via Docker Images.
5.) Recognizing & maintaining business standards for accuracy, productivity & and managing resources & operations daily to ensure timely adherence to SLAs
6.) Promoting change and driving strategic initiatives through strong partnerships across the organization, displaying personal resilience and skills to lead through change, creating a shared vision by building joint ownership.
7.) Creating high-impact Data Science Projects and coordinating with stakeholders, leading a potentially cross-functional team in providing the best solution to a given problem
8.) Applying research methodologies to identify the machine learning problems & developing AI\ML models for defined solutions
9.) Maintaining standard documentation for all the process and collaborating with engineering, marketing, product management, and customers
10.) Acting as a valued contributor in product discussions and educating the company about data science by delivering impactful data science solution.