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I'm Jarod Wilson, a Senior AI/ML and Python Backend Engineer with 10+ years of experience building scalable, production-grade machine learning systems and cloud-native backend architectures. I'm proficient in Python, FastAPI, TensorFlow, PyTorch, and AWS, with a strong background in data engineering, API design, and MLOps. I have hands-on experience deploying LLM and RAG-based applications, optimizing model performance, and integrating AI workflows into enterprise software solutions. I enjoy turning business requirements into measurable technical outcomes by designing data-driven architectures and collaborating across cross-functional teams to accelerate AI adoption.…I'm Jarod Wilson, a Senior AI/ML and Python Backend Engineer with 10+ years of experience building scalable, production-grade machine learning systems and cloud-native backend architectures. I'm proficient in Python, FastAPI, TensorFlow, PyTorch, and AWS, with a strong background in data engineering, API design, and MLOps. I have hands-on experience deploying LLM and RAG-based applications, optimizing model performance, and integrating AI workflows into enterprise software solutions. I enjoy turning business requirements into measurable technical outcomes by designing data-driven architectures and collaborating across cross-functional teams to accelerate AI adoption.

Jarod Wilson

AI Engineer, Data Scientist, Back-End Developer, +1

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I'm Jarod Wilson, a Senior AI/ML and Python Backend Engineer with 10+ years of experience building scalable, production-grade machine learning systems and cloud-native backend architectures. I'm proficient in Python, FastAPI, TensorFlow, PyTorch, and AWS, with a strong background in data engineering, API design, and MLOps. I have hands-on experience deploying LLM and RAG-based applications, optimizing model performance, and integrating AI workflows into enterprise software solutions. I enjoy turning business requirements into measurable technical outcomes by designing data-driven architectures and collaborating across cross-functional teams to accelerate AI adoption.…I'm Jarod Wilson, a Senior AI/ML and Python Backend Engineer with 10+ years of experience building scalable, production-grade machine learning systems and cloud-native backend architectures. I'm proficient in Python, FastAPI, TensorFlow, PyTorch, and AWS, with a strong background in data engineering, API design, and MLOps. I have hands-on experience deploying LLM and RAG-based applications, optimizing model performance, and integrating AI workflows into enterprise software solutions. I enjoy turning business requirements into measurable technical outcomes by designing data-driven architectures and collaborating across cross-functional teams to accelerate AI adoption.

Available to hire

I’m Jarod Wilson, a Senior AI/ML and Python Backend Engineer with 10+ years of experience building scalable, production-grade machine learning systems and cloud-native backend architectures. I’m proficient in Python, FastAPI, TensorFlow, PyTorch, and AWS, with a strong background in data engineering, API design, and MLOps.

I have hands-on experience deploying LLM and RAG-based applications, optimizing model performance, and integrating AI workflows into enterprise software solutions. I enjoy turning business requirements into measurable technical outcomes by designing data-driven architectures and collaborating across cross-functional teams to accelerate AI adoption.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

Senior AI/ML & Backend Engineer at Qubika

January 1, 2023 - Present

Directed an 8-member cross-functional team to design and deploy AI-native apps using Python, FastAPI, and AWS, maintaining 99.9% uptime and supporting enterprise-grade scalability. Architected agentic AI systems leveraging LangChain, OpenAI, and RAG pipelines, enabling clients in finance, healthcare, and high-tech to automate workflows and reduce processing time by 45%. Led the development of Accelerate AI modules, integrating Airflow, Databricks, and Snowflake pipelines to deliver 30% faster model deployment and more reliable data synchronization. Mentored junior engineers on MLOps and distributed systems, improving delivery efficiency by 25% and reducing code review turnaround time. Implemented Prometheus and Grafana for real-time monitoring and alerting; built LLM fine-tuning frameworks using BERT and FLAN-T5; optimized backend infrastructure with Kubernetes and asynchronous APIs; contributed to internal R&D on AI agents and vector databases (Pinecone, FAISS).

AI/ML Engineer at Hatch Works AI

June 1, 2018 - December 1, 2022

Delivered end-to-end generative AI and ML solutions for enterprise clients, focusing on agentic workflows and RAG-based architectures. Architected data pipelines and feature stores with Airflow 2, AWS Glue, and Snowflake; internal AI orchestration framework to manage multiple LLMs and vector stores (Pinecone, FAISS), improving information retrieval accuracy by 35%. Collaborated with cross-functional teams to fine-tune domain-specific LLMs and integrate them into client products, reducing manual work by 40%. Implemented MLOps with MLflow and Docker, achieving 30% deployment-time reduction and better model governance. Contributed to R&D exploring AI agents and automated prompting for enterprise use cases.

Machine Learning Engineer at BlueLabel

February 1, 2016 - May 1, 2018

Developed and deployed ML models for predictive analytics and data-driven insights using Python, TensorFlow v2.2, and scikit-learn. Created data transformation pipelines with AWS S3, Glue, and Lambda to support model training and deployment. Built RESTful APIs for AI-driven features using FastAPI and Flask, enabling real-time model integration for 50K+ active users. Prototyped and tested AI features with teams, reducing product iteration time by 20%. Containerized services with Docker and automated CI/CD pipelines on AWS for reliable deployment.

Data Scientist at Experience Technologies

July 1, 2014 - January 1, 2016

Designed and automated ETL pipelines ingesting multi-source data into AWS S3/Redshift, improving data reliability and reducing latency by 30%. Optimized pipelines and SQL queries to reduce processing time by 30% through parallelization and indexing; supported data science with structured datasets reducing model training time by 20% and ensuring 100% data integrity in production pipelines.

Data Scientist at Experio Technologies

July 1, 2014 - January 1, 2016

Designed and automated ETL pipelines ingesting multi-source data into AWS S3/Redshift, improving data reliability and reducing latency by 30%. Optimized data pipelines, reducing processing time by 30% through efficient SQL queries and task parallelization. Enhanced SQL-based query performance by 25% through parallelization and indexing. Supported the data science team by preparing structured datasets that reduced model training time by 20%. Developed data validation scripts ensuring 100% data integrity in production pipelines.