Azhan K.

Key Skills

Software

Other

Scale AI

Top Subject Matter

Autonomous driving / ML training data (multi-modal sensor/video/telemetry)

Data engineering for dataset reliability (non-explicit labeling)

Top Data Types

3D Sensor

Video

Top Task Types

Data Collection

Tracking

Freelancer Overview

Data & AI Operations Engineer — Zensar Technologies (Client: NVIDIA). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other and Scale AI. Education includes Bachelor of Technology, Nri Institute of Technology, Bhopal (2025). AI-training focus includes data types such as 3D Sensor, Computer Code, and Programming and labeling workflows including Data Collection and Tracking.

Labeling Experience

Data and AI Operations Engineer - Zensar Technologies

Scale AIVideoTracking

Collaborated with senior ML engineers to build and maintain large-scale AI training data pipelines for NVIDIA's autonomous driving program, processing 100K+ real-world multi-modal records. Developed data validation and quality frameworks enforcing schema consistency and label accuracy, reducing data defect rates by ~35% across training batches. Designed transformation workflows converting raw driving scenario logs into structured, ML-ready datasets while working with cloud-based platforms and large-scale data. • Supported schema and label accuracy validation processes • Implemented transformation and dataset preparation workflows • Worked with multi-modal sensor, video, and telemetry data at scale • Documented edge-case patterns to improve dataset coverage and robustness

2025 - 2026

Data & AI Operations Engineer — Zensar Technologies (Client: NVIDIA)

Other3D SensorData Collection

You worked on preparing and maintaining large-scale AI training datasets for NVIDIA autonomous driving, including collecting and structuring multi-modal records. You focused on ensuring the correctness of labels by building and applying data validation and quality frameworks for schema consistency and label accuracy. You transformed raw driving scenario logs into ML-ready datasets for downstream model training. • Processed 100K+ real-world multi-modal records (sensor, video, telemetry). • Enforced schema consistency and label accuracy via validation/quality frameworks. • Converted raw scenario logs into structured datasets using transformation workflows. • Documented edge-case patterns to improve training coverage and robustness.

2025 - 2026

Data Engineer Intern — Netlink Software Group America Inc.

OtherData Collection

You built production ETL pipelines intended to produce reliable datasets for downstream use. You optimized data processing workflows to improve throughput and reduce latency. You worked with senior engineers to align outputs with data reliability standards. • Developed ETL pipelines using Python with DuckDB and Alembic. • Followed SDLC best practices alongside senior engineering support. • Improved throughput and reduced latency for data processing. • Contributed to producing dependable datasets for downstream consumers.

2025 - 2025

Education

Work History