Software Engineer, ML engineer candidate in Raleigh, North Carolina, United States

Summary

Software Developer Crispin Corporation (Jan 2024 Present)

Designed and deployed AI-driven systems using deep learning, NLP, and LLM-based workflows to automate large-scale data analysis and decision-support processes.

Built and productionized Python-based ML pipelines leveraging vector embeddings and retrieval-augmented generation (RAG) techniques for intelligent data querying and contextual reasoning.

Developed scalable backend microservices (FastAPI, Docker, Kubernetes) supporting AI model inference and orchestration in cloud environments (AWS).

Implemented anomaly detection and statistical monitoring systems to proactively identify operational risks and data inconsistencies.

Collaborated cross-functionally with engineering, QA, and domain stakeholders to translate complex business requirements into reliable AI-powered solutions.
Python Developer Mobile Smith Health (Dec 2022 Nov 2023)

Developed Python-based healthcare data pipelines for ingestion, transformation, and analytics of clinical and operational datasets using SQLAlchemy and PostgreSQL.

Built RESTful APIs to support healthcare-focused applications, enabling efficient processing of structured and semi-structured patient and operational data, Supported automation of data workflows to improve operational efficiency within healthcare systems

Leveraged Pandas and NumPy for statistical analysis and data quality validation.
Software Engineer ML, SparkCognition (Jun 2022 Nov 2022)

Developed FastAPI-based ML services supporting model training, evaluation, and deployment workflows for scalable AI systems.

Implemented deep learning experimentation workflows including hyperparameter tuning and model performance optimization.

Managed asynchronous data and model processing pipelines to handle large-scale datasets efficiently.

Containerized and deployed AI services using Docker and Kubernetes with CI/CD pipelines for robust, production-grade releases.

Contributed to scalable ML infrastructure enabling rapid experimentation and deployment of AI solutions.

Expectations

Im looking for a role that builds on my experience designing and deploying AI-driven systems while pushing me to grow technically and professionally. In my next position, I expect to work on meaningful, real-world problems where machine learning and backend engineering can create measurable impact. Im particularly interested in opportunities that involve scalable AI systems, such as LLM-based applications, data pipelines, and cloud-native architectures.

I value an environment that encourages ownership and innovation, where I can contribute to system design decisions, improve existing processes, and help drive projects from concept to production. Access to modern tools, well-structured engineering practices, and a strong emphasis on code quality and reliability are also important to me.

Collaboration is another key expectation. I want to work with cross-functional teams where ideas are openly shared, and feedback is constructive, enabling continuous improvement. At the same time, I appreciate a culture that supports learningwhether through mentorship, knowledge sharing, or opportunities to explore emerging technologies.

Finally, Im seeking a role that offers both technical challenges and career growth, allowing me to deepen my expertise in AI/ML systems while expanding my impact within the organization.