Lokeswar K profile photo 2 on Tal
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Lokeswar K profile photo 2 on Tal
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Lokeswar K

Data Engineer @ IBM | Azure · Databricks · Snowflake · PySpark | ML/AI Enthusiast | Passionate About Building Things from the Ground Up

India

2+ years of work experience

IBM
Jan 20251 yr 8 mosPresent

Bengaluru, Karnataka, India

• Designed and implemented scalable ETL/ELT pipelines using Azure Data Factory, Databricks, Snowflake, and PySpark, supporting multi-source data ingestion and transformation across enterprise workflows. • Re-architected a compute-intensive automation from Databricks to Azure Logic Apps, reducing cloud compute costs by ~CA$1,500 per week while improving reliability and maintainability. • Developed a reusable automation framework for file monitoring, exception handling, and incident management, reducing manual operational effort by over 80%. • Built a real-time SLA monitoring and alerting solution using Power Automate and Microsoft Teams, helping maintain zero SLA breaches across production pipelines. • Improved production reliability through automation, monitoring, and operational enhancements, enabling faster issue detection and response across critical data workflows.
Dev TV
Oct 20243 mosDec 2024

Remote

Built Generative AI workflows using Flux AI, ComfyUI, and LoRA fine-tuning for hyper-realistic image generation. • Trained and optimized custom LoRA models on cloud GPU infrastructure (RunPod) for character-consistent image generation. • Developed end-to-end image generation pipelines integrating diffusion models, ControlNets, upscaling, and realism-enhancement models. • Leveraged Google Colab and cloud-based AI environments to streamline model training, deployment, and experimentation. Skills: Generative AI, LoRA Fine-Tuning, Diffusion Models, ComfyUI, Flux AI, RunPod, Google Colab, Prompt Engineering
Mistral Solutions Pvt. Ltd
May 20232 mosJun 2023

Bengaluru, Karnataka, India

• Worked on one of the company's early Machine Learning initiatives involving 77GHz radar-based human activity recognition using radar point-cloud data. • Developed deep learning models using Time-Distributed CNN and Bidirectional LSTM architectures to classify and predict human activities from radar sensor data. • Built data processing workflows to transform raw radar point-cloud data collected through ROS into ML-ready datasets for model training and evaluation. • Contributed to demonstrating the feasibility of applying AI/ML techniques to radar sensing applications, supporting future development of intelligent radar-based solutions. • Collaborated with cross-functional teams in a research-oriented environment to develop and validate end-to-end ML solutions.

Lokeswar’s AI Stack

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claude code
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claude
ChatGPT
ChatGPT
FLUX
FLUX

Education

Vellore Institute of Technology (VIT)

Bachelor's degree, Electrical and Electronics Engineering

Vellore Institute of Technology (VIT)

20204 yrs2024

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Headline

Data Engineer @ IBM | Azure · Databricks · Snowflake · PySpark | ML/AI Enthusiast | Passionate About Building Things from the Ground Up

About

Data Engineer at IBM working on cloud-based data platforms, automation, and production data workflows using Azure, Databricks, Snowflake, PySpark, Python, and SQL. Over the last 1.5 years, I've contributed to initiatives that reduced cloud compute costs by CA$1,500/week, cut manual operational effort by 80%+, and helped maintain zero SLA breaches across production processes. My work spans ETL pipelines, data quality, monitoring, automation, and large-scale data processing. I'm particularly interested in the intersection of Data Engineering, Machine Learning, and AI. During my internship at Mistral Solutions, I worked on one of the company's early ML initiatives involving radar-based human activity recognition, developing CNN-BiLSTM models on radar point-cloud data to classify human activities and demonstrate the potential of ML-powered radar sensing applications. I'm a strong believer in learning by building and continuously explore areas such as ML systems, MLOps, real-time data platforms, and AI infrastructure. Stack: Azure Data Factory • Databricks • PySpark • Snowflake • Delta Lake • Python • SQL 📍 Bengaluru · Open to Data Engineer, ML Engineer, AI Engineer, and ML Platform opportunities.

Location

India

AI stack

claude code

claude

ChatGPT

FLUX

Work experience

Data Engineer at IBM, Jan 2025 - Present · 1 yr 8 mos, Bengaluru, Karnataka, India, • Designed and implemented scalable ETL/ELT pipelines using Azure Data Factory, Databricks, Snowflake, and PySpark, supporting multi-source data ingestion and transformation across enterprise workflows. • Re-architected a compute-intensive automation from Databricks to Azure Logic Apps, reducing cloud compute costs by ~CA$1,500 per week while improving reliability and maintainability. • Developed a reusable automation framework for file monitoring, exception handling, and incident management, reducing manual operational effort by over 80%. • Built a real-time SLA monitoring and alerting solution using Power Automate and Microsoft Teams, helping maintain zero SLA breaches across production pipelines. • Improved production reliability through automation, monitoring, and operational enhancements, enabling faster issue detection and response across critical data workflows.

Artificial Intelligence Intern at Dev TV, Oct 2024 - Dec 2024 · 3 mos, Remote, Built Generative AI workflows using Flux AI, ComfyUI, and LoRA fine-tuning for hyper-realistic image generation. • Trained and optimized custom LoRA models on cloud GPU infrastructure (RunPod) for character-consistent image generation. • Developed end-to-end image generation pipelines integrating diffusion models, ControlNets, upscaling, and realism-enhancement models. • Leveraged Google Colab and cloud-based AI environments to streamline model training, deployment, and experimentation. Skills: Generative AI, LoRA Fine-Tuning, Diffusion Models, ComfyUI, Flux AI, RunPod, Google Colab, Prompt Engineering

Software Engineer at Mistral Solutions Pvt. Ltd, May 2023 - Jun 2023 · 2 mos, Bengaluru, Karnataka, India, • Worked on one of the company's early Machine Learning initiatives involving 77GHz radar-based human activity recognition using radar point-cloud data. • Developed deep learning models using Time-Distributed CNN and Bidirectional LSTM architectures to classify and predict human activities from radar sensor data. • Built data processing workflows to transform raw radar point-cloud data collected through ROS into ML-ready datasets for model training and evaluation. • Contributed to demonstrating the feasibility of applying AI/ML techniques to radar sensing applications, supporting future development of intelligent radar-based solutions. • Collaborated with cross-functional teams in a research-oriented environment to develop and validate end-to-end ML solutions.

Education

Bachelor's degree, Electrical and Electronics Engineering, Vellore Institute of Technology (VIT)

Lokeswar K - Data Engineer in India | Tal