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Hi, I’m Bhavarth Bhangdia. I’m a machine learning engineer focused on scaling AI systems and delivering measurable business impact. I enjoy turning complex research into practical, reliable products that users can trust, especially in generative AI, model deployment, and data-driven optimization. Outside work, I’m curious and collaborative, always looking for ways to mentor teammates and learn from others. I value clean experimentation, reproducible pipelines, and clear communication to align engineering, product, and operations toward shared goals.…Hi, I’m Bhavarth Bhangdia. I’m a machine learning engineer focused on scaling AI systems and delivering measurable business impact. I enjoy turning complex research into practical, reliable products that users can trust, especially in generative AI, model deployment, and data-driven optimization. Outside work, I’m curious and collaborative, always looking for ways to mentor teammates and learn from others. I value clean experimentation, reproducible pipelines, and clear communication to align engineering, product, and operations toward shared goals.

Bhavarth Bhangdia

AI Engineer, Data Scientist, Programmer

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Hi, I’m Bhavarth Bhangdia. I’m a machine learning engineer focused on scaling AI systems and delivering measurable business impact. I enjoy turning complex research into practical, reliable products that users can trust, especially in generative AI, model deployment, and data-driven optimization. Outside work, I’m curious and collaborative, always looking for ways to mentor teammates and learn from others. I value clean experimentation, reproducible pipelines, and clear communication to align engineering, product, and operations toward shared goals.…Hi, I’m Bhavarth Bhangdia. I’m a machine learning engineer focused on scaling AI systems and delivering measurable business impact. I enjoy turning complex research into practical, reliable products that users can trust, especially in generative AI, model deployment, and data-driven optimization. Outside work, I’m curious and collaborative, always looking for ways to mentor teammates and learn from others. I value clean experimentation, reproducible pipelines, and clear communication to align engineering, product, and operations toward shared goals.

Next availability:

December 24, 2025

United Kingdom

Hi, I’m Bhavarth Bhangdia. I’m a machine learning engineer focused on scaling AI systems and delivering measurable business impact. I enjoy turning complex research into practical, reliable products that users can trust, especially in generative AI, model deployment, and data-driven optimization.

Outside work, I’m curious and collaborative, always looking for ways to mentor teammates and learn from others. I value clean experimentation, reproducible pipelines, and clear communication to align engineering, product, and operations toward shared goals.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

ML Engineer at PIXLR

August 1, 2024 - November 26, 2025

Owned end-to-end optimization of generative AI inference pipelines, reducing P95 latency by 76% (33s to 7.9s) through quantization, attention pruning, and ONNX-TensorRT deployment; automated resource allocation using historical data to boost GPU utilization from 46% to 81%. Led design and deployment of predictive voice cloning models with 10M+ hours of data, and built automated validation pipelines for large-scale analysis. Architected real-time multi-GPU schedulers with NCCL and Ray Serve, delivering 2.2x throughput gains and coordinated with Ops to cut infra costs by 30% via spot-instance routing and custom benchmarking. Spearheaded video model evaluation acceleration for 12K samples, integrating AI-driven evaluation pipelines and mentoring cross-functional teams on ML deployment practices.

AI Coder at SCALE AI

March 1, 2024 - March 1, 2024

Designed rubrics and led A/B testing for code-suggestion models across 12K samples, raising acceptance rates to 92% by balancing style and correctness via unit-test templates; led ablation studies to refine evaluation metrics. Directed vectorization and cache-optimized batching, halving P95 job times from 74 to 36 minutes and doubling throughput; built automated validation tools to improve annotation quality and mentored the team.

Data Science Intern at ALPHAA AI

December 31, 2023 - December 31, 2023

Engineered a random forest classifier to predict customer churn, achieving 85% accuracy and driving a targeted retention campaign that reduced churn by 8%. Executed probabilistic risk modeling with backtesting, increasing team confidence from 6/10 to 9/10 via reproducible notebooks and end-to-end model ownership playbooks.