Jared Cameron Stanley
Verified Expert in Engineering
AI Engineer and Developer
Denver, CO, United States
Toptal member since July 1, 2020
Jared is a senior AI engineer and solutions architect with 12+ years’ experience building high-impact AI systems across healthcare, defense, energy, and tech. He specializes in GenAI/LLM productization (RAG, agents, and system integrations), data strategy and pipeline development, and scalable production machine learning (ML) systems. Jared's goal is to help you define the right AI strategy and ship production-grade solutions that drive measurable outcomes.
Portfolio
Experience
- Data Analytics - 11 years
- Python - 11 years
- Data Science - 11 years
- Deep Learning - 8 years
- Machine Learning - 8 years
- Artificial Intelligence (AI) - 8 years
- SQL - 7 years
Preferred Environment
Deep Learning, Python, Spark, Machine Learning, Artificial Intelligence (AI), Data Science, SQL, Generative Artificial Intelligence (GenAI), Large Language Models (LLMs)
The most amazing...
...solutions I have built have been possible through a strong collaboration with stakeholders and a deep understanding of business goals.
Work Experience
Founder and CEO
Adinkra
- Grew and managed a team of 15+ analytics, engineering, marketing, and administrative staff to develop AI, data science, and machine learning solutions for clients in the healthcare, defense, and energy industries.
- Built an autonomous drone, complete with custom navigation, perception, control, and end-to-end simulation tools. Demonstrated real-world solutions for major defense companies and helped clients secure $10+ million in funding.
- Created an AI application for warehouse monitoring, including tools for data annotation, active learning, synthetic data generation, and edge deployment. Deployed to 1,000+ sites with estimated savings in the millions/year for operators.
- Developed a disease outbreak model, a patient marketing optimization model, and a COVID-19 distribution optimization model for a large US retailer. These models impacted over 100+ million customers and 10,000 stores daily.
- Created a big data solution for wind turbines and then used this to develop a yaw alignment optimization algorithm deployed to 1,000+ turbines, which saves $10+ million annually in OpEx.
Senior Data Scientist
Orsted Onshore Asset Management Services, LLC
- Developed physics-based turbine yaw optimization model using Spark, saving $10+ million in OpEx each year.
- Automated engineering data ingest pipelines for 1,000+ turbines in the US.
- Created real-time analytics dashboards for key stakeholders to monitor operations, align with SCADA data, and detect issues early for on-site teams.
Deep Learning Engineer
Two Impulse
- Created an application for data scientists to train, predict, and manage machine learning model notebooks.
- Implemented state-of-the-art multilingual NLP deep learning models (e.g., sentiment analysis, topic analysis, NER).
- Reduced data set annotation time by around 70% using online learning.
Senior Data Scientist
Guidehouse
- Built a state-wide asset risk model to inform over $1 billion in grid resiliency planning. This included weather modeling, asset risk modeling, graph analytics, and ingestion of processing of thousands of engineering and business documents.
- Drove internal adoption of Spark practice-wide by creating a robust standard error package in Spark, automating TB of streaming data, and deploying a complex dynamic time-warping algorithm for end-user segmentation.
- Built a traffic accident risk model to save around $25 million a year for the Hawaii utility using road, weather, utility, and traffic data.
- Led development of a Bass diffusion model for forecasting electric vehicle (EV) adoption and EV siting analysis using Python and ArcGIS. Optimized over $10 million in EVSE infrastructure for large EV companies.
- Built a machine learning model to predict window stock, turnover, and efficiency changes in the United States using Bayesian inference. The automated approach allowed us to reduce client project costs by around 40% and save around 60 TBtu per year.
Data Engineer
PwC
- Architected the enterprise ETL solution to extract data from data lakes and major ERPs, process it using ephemeral MemSQL clusters, and update data warehouses. Included REST APIs, Airflow, and Dynamic SQL.
- Developed a custom QC and testing suite in Python to perform regression, integration, and unit testing. Quality checks and Type 2 tracking ensured the highest data integrity.
- Developed process mining and outlier analysis tools, including custom dashboards using D3 and Zoom.
Software Engineer
Payger
- Created a blockchain-based payments platform on the Graphene network, achieving around 10x faster settlement times compared to traditional banks.
- Developed a companion block explorer application for real-time transaction monitoring.
- Created technical demos and marketing materials for conferences and expos.
Research Associate (Physics)
Various
- Worked as a physics researcher for several institutions, including the Laboratory for Atmospheric and Space Physics (LASP), Max Planck Institute for Plasma Physics (MPI), Walter Schottky Institute (WSI), Technical University of Munich, and CU Boulder.
- Created machine learning models to analyze lunar dust physics and build a next-generation mass spectrometer.
- Developed machine learning models and software to automate optical experiment analysis from Tokamak data.
- Developed an AI-based system to discover and optimize new photovoltaic materials.
- Developed custom imaging, computer vision, and software analysis solutions to optimize semiconductor manufacturing.
Experience
Machine Learning Perovskites
https://github.com/jstanai/Machine-Learning-Perovskite-Properties-for-PhotovoltaicsTidyspark
https://github.com/danzafar/tidysparkMovie Rental Application
https://github.com/jstanai/Video-Rental-ApplicationEducation
Master of Science Degree in Applied and Engineering Physics
Technical University of Munich - Munich, Germany
Bachelor of Arts Degree in Physics (Minor in Mathematics)
University of Colorado Boulder - Boulder, Colorado, USA
Certifications
Deep Learning Specialization
Coursera
The Complete Node.js Course
Code With Mosh
UC San Diego Big Data Specialization
Coursera
Skills
Libraries/APIs
PySpark, TensorFlow, Keras, REST APIs, SpaCy, OpenCV, Pandas, NumPy, Scikit-learn, PyTorch, Node.js
Tools
Git, Plotly, GitHub, Apache Airflow, sparklyr, Jupyter, Kibana, CAD
Languages
Python, SQL, R, Markdown, Java
Frameworks
Spark, RStudio Shiny, Apache Spark, Hadoop, Flask
Paradigms
Anomaly Detection, REST
Platforms
Jupyter Notebook, MacOS, Windows, Visual Studio Code (VS Code), RStudio, Docker, Blockchain, Amazon Web Services (AWS), Databricks, Azure, Google Cloud Platform (GCP)
Industry Expertise
Project Management
Storage
MongoDB, Elasticsearch, MemSQL, MySQL
Other
Data Science, Machine Learning, Consulting, Deep Learning, Computer Vision, Artificial Intelligence (AI), Robotics, Modeling, Mathematics, Research, Convolutional Neural Networks (CNNs), Natural Language Processing (NLP), Recurrent Neural Networks (RNNs), MLflow, Data Engineering, Data Analytics, Data Visualization, AI Design, Deep Neural Networks (DNNs), Computer Vision Algorithms, Neural Networks, Generative Pre-trained Transformers (GPT), Statistical Modeling, Statistics, Big Data, EOS, Bayesian Statistics, Software Development, Analytics, Product Development, Software, Renewable Energy, Electrical Engineering, Log4j, Simulations, Web Applications, Generative Artificial Intelligence (GenAI), Causal AI, LangChain, Large Language Models (LLMs), Time Series
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