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I’m a data-driven AI/ML engineer focused on building scalable, production-grade AI systems. I enjoy turning cutting-edge research into robust platforms using Python, PyTorch, TensorFlow, and cloud-native infrastructures. I’ve designed predictive maintenance and anomaly-detection solutions, RLHF-aligned language models, and end-to-end AI pipelines that scale across thousands of assets in industrial settings. I thrive in cross-functional teams and love translating research into practical tools for real-world impact. My strengths include building robust data pipelines, evaluating models rigorously, and delivering observable, reliable AI systems on AWS, Kubernetes, and distributed compute platforms. I’m passionate about continuous learning and mentoring teams to ship high-quality AI solutions at scale.…I’m a data-driven AI/ML engineer focused on building scalable, production-grade AI systems. I enjoy turning cutting-edge research into robust platforms using Python, PyTorch, TensorFlow, and cloud-native infrastructures. I’ve designed predictive maintenance and anomaly-detection solutions, RLHF-aligned language models, and end-to-end AI pipelines that scale across thousands of assets in industrial settings. I thrive in cross-functional teams and love translating research into practical tools for real-world impact. My strengths include building robust data pipelines, evaluating models rigorously, and delivering observable, reliable AI systems on AWS, Kubernetes, and distributed compute platforms. I’m passionate about continuous learning and mentoring teams to ship high-quality AI solutions at scale.

Sai Adarsh Malla

AI Engineer, Full Stack Developer, Data Scientist, +2

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I’m a data-driven AI/ML engineer focused on building scalable, production-grade AI systems. I enjoy turning cutting-edge research into robust platforms using Python, PyTorch, TensorFlow, and cloud-native infrastructures. I’ve designed predictive maintenance and anomaly-detection solutions, RLHF-aligned language models, and end-to-end AI pipelines that scale across thousands of assets in industrial settings. I thrive in cross-functional teams and love translating research into practical tools for real-world impact. My strengths include building robust data pipelines, evaluating models rigorously, and delivering observable, reliable AI systems on AWS, Kubernetes, and distributed compute platforms. I’m passionate about continuous learning and mentoring teams to ship high-quality AI solutions at scale.…I’m a data-driven AI/ML engineer focused on building scalable, production-grade AI systems. I enjoy turning cutting-edge research into robust platforms using Python, PyTorch, TensorFlow, and cloud-native infrastructures. I’ve designed predictive maintenance and anomaly-detection solutions, RLHF-aligned language models, and end-to-end AI pipelines that scale across thousands of assets in industrial settings. I thrive in cross-functional teams and love translating research into practical tools for real-world impact. My strengths include building robust data pipelines, evaluating models rigorously, and delivering observable, reliable AI systems on AWS, Kubernetes, and distributed compute platforms. I’m passionate about continuous learning and mentoring teams to ship high-quality AI solutions at scale.

Available to hire

I’m a data-driven AI/ML engineer focused on building scalable, production-grade AI systems. I enjoy turning cutting-edge research into robust platforms using Python, PyTorch, TensorFlow, and cloud-native infrastructures. I’ve designed predictive maintenance and anomaly-detection solutions, RLHF-aligned language models, and end-to-end AI pipelines that scale across thousands of assets in industrial settings.

I thrive in cross-functional teams and love translating research into practical tools for real-world impact. My strengths include building robust data pipelines, evaluating models rigorously, and delivering observable, reliable AI systems on AWS, Kubernetes, and distributed compute platforms. I’m passionate about continuous learning and mentoring teams to ship high-quality AI solutions at scale.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

AI/ML Engineer at Scale AI

April 1, 2026 - Present

Led AI/ML engineering for large language model alignment and preference-learning systems (RLHF) using PyTorch, Transformers, and Ray; designed evaluation pipelines with 12M+ human feedback interactions, improving reasoning quality and response accuracy by ~18%; built cloud-native ML platforms on AWS with EKS, S3, Terraform, Prometheus, Grafana, and OpenTelemetry; developed end-to-end MLOps pipelines enabling rapid experimentation and scalable model serving across distributed environments.

AI/ML Engineer at NVIDIA

April 1, 2024 - April 1, 2026

Architected AI systems and ML pipelines for large-language-model training, evaluation, and real-time inference across production environments. Built large-scale world-model training pipelines using PyTorch, NVIDIA Nemo, Megatron-LM, enabling multimodal foundation models. Implemented distributed training across multi-node clusters with Ray, PyTorch FSDP, and HuggingFace Transformers; created scalable data-curation and evaluation frameworks; designed cloud-native microservices with Docker, Kubernetes, FastAPI, and gRPC; enabled real-time inference orchestration and end-to-end MLOps workflows in AWS-based infrastructure.

AI/ML Engineer

August 1, 2020 - July 1, 2023

Engineered predictive maintenance and anomaly-detection solutions using Python, PySpark, XGBoost, and AWS data platforms; built time-series forecasting and asset-health scoring models; designed scalable data engineering pipelines using PySpark and Spark SQL to ingest, transform, and process IoT sensor streams from thousands of connected assets. Implemented end-to-end ML workflows, real-time inference, alert generation, and automated model evaluation to improve maintenance efficiency and reduce downtime.