Open to opportunities

Juned A

@juneda

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Senior Machine Learning Engineer specializing in cloud-native MLOps, NLP, and applied AI research.

United States

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What I'm looking for

I seek senior roles building production ML systems and cloud-native MLOps, focusing on scalable model deployment, observability, and impactful AI solutions in healthcare or industrial domains.

I am a Senior Machine Learning Engineer and Applied AI Researcher with 13+ years of experience building scalable AI/ML solutions across healthcare, industrial automation, and enterprise domains.

I design and deploy production-grade ML pipelines and models — from Transformer-based NLP and LLM fine-tuning to computer vision and multi-sensor perception — using tools like PyTorch, TensorFlow, Hugging Face, and FastAPI.

My MLOps practice focuses on cloud-native deployments and observability: containerized services with Docker and Kubernetes, experiment tracking with MLflow and W&B, CI/CD with GitHub Actions, and monitoring with Grafana and Prometheus.

I have delivered HIPAA-compliant healthcare solutions, developed automated retraining and auto-labeling workflows, and led initiatives in reinforcement learning, anomaly detection, and feature-rich time-series forecasting to drive measurable business impact.

Experience

Work history, roles, and key accomplishments

Current

Senior Machine Learning Engineer

Current

Klarity Labs

May 2024 - Present (2 years 1 month)

Designed and deployed LLM and Transformer-based NLP models and cloud-native ML APIs, implemented real-time inference monitoring and automated retraining pipelines, and experimented with RL algorithms to optimize real-time decision-making for sensor-driven environments.

PyTorch Hugging Face fastAPI Docker AWS Lambda MLFlow Prometheus Grafana Reinforcement Learning

Machine Learning Engineer

Tech Innovate Sonctions

Feb 2021 - Apr 2024 (3 years 2 months)

Developed recommendation, classification, and regression models, managed distributed training infrastructure with autoscaling on AWS/GCP, and built ETL pipelines and MLflow-backed experimentation to integrate ML into customer-facing applications.

PyTorch scikit learn AWS GCP Airflow SQL MLFlow Distributed Training MLOps

Machine Learning Engineer

ZestyAI

Jan 2019 - Dec 2020 (1 year 11 months)

Built time-series forecasting and predictive analytics solutions, created MLOps pipelines using Azure ML/Databricks/AKS, implemented explainability dashboards, and developed streaming anomaly detection and AutoML tooling for distributed GPU workloads.

Databricks AKS ARIMA SHAP LIME AutoML

AI Developer

NextGen Analytics

Mar 2012 - Dec 2018 (6 years 9 months)

Developed computer vision models (YOLO, CNNs) and OCR document parsing, packaged AI models as microservices with Flask/Docker, and automated training workflows to support industrial defect detection and sensor-fusion perception prototypes.

Sensor Fusion YOLO CNN OpenCV Flask Docker Sensor Fusion Version Control