Open to opportunities

Aiden Brooks

@aidenbrooks

Message

I am a Senior Machine Learning Engineer focused on production-ready MLOps solutions.

United States

Message

What I'm looking for

I seek senior ML/MLOps roles where I can design, deploy, and scale production AI systems, mentor teams, and champion responsible AI in cloud-native environments.

I am an innovative, results-driven Machine Learning Engineer with over 10 years of experience designing, developing, and deploying scalable, data-driven solutions across aviation, healthcare, and finance.

I specialize in building production-ready ML pipelines and real-time predictive systems using modern MLOps practices and cloud-native ML platforms such as AWS SageMaker, GCP Vertex AI, and Azure ML.

I have deployed scalable ML pipelines for flight delay prediction, led the design and deployment of a real-time recommendation engine that improved revenue, built NLP models that increased customer satisfaction, and integrated ML observability into CI/CD to reduce deployment bugs.

I enjoy mentoring junior engineers, leading cross-functional teams, and operationalizing AI responsibly—ensuring fairness, transparency, and reproducibility—and hold certifications including AWS Certified Machine Learning Specialty, TensorFlow Developer Certificate, and Google Professional Data Engineer.

Experience

Work history, roles, and key accomplishments

Current

Senior Machine Learning Engineer

Current

DeltaTech Solutions

Oct 2024 - Present (10 months)

Deployed scalable ML pipelines using AWS SageMaker and Lambda for flight delay prediction and led design of a real-time recommendation engine for ticket pricing that improved airline revenue. Mentored junior engineers and ran internal MLOps and model governance workshops to operationalize models.

Python AWS Sagemaker Lambda MLOps Model Governance TensorFlow Mentoring

Machine Learning Engineer

PeachAI Analytics

Feb 2021 - Sep 2024 (3 years 7 months)

Built NLP sentiment models for customer feedback that increased satisfaction scores and developed XGBoost classifiers with cross-validation and hyperparameter tuning. Automated data cleaning and feature engineering with Airflow and collaborated with data engineering to reduce pipeline processing time.

Python NLP XGBoost scikit learn Airflow Cross Validation Hyperparameter Tuning Data Pipelines

Machine Learning Research Engineer

DeepMind

Dec 2019 - Jan 2021 (1 year 1 month)

Contributed to large-scale reinforcement learning experiments for healthcare forecasting and built reproducible TFX pipelines with ML Metadata for experiment tracking. Collaborated with Google Cloud teams to deploy high-throughput inference systems and ensured GDPR/HIPAA-compliant research-to-production transitions.

Reinforcement Learning TensorFlow Metadata Google Cloud GDPR HIPAA

Data Science Consultant

NeuroCloud Inc.

Aug 2016 - Nov 2019 (3 years 3 months)

Consulted on anomaly detection systems for cloud infrastructure and developed time-series forecasting models for resource usage and capacity planning to improve allocation. Integrated ML observability into CI/CD pipelines and presented technical findings to senior stakeholders.