Founder Resume

Vladimir Rife

AI/ML Contractor & Engineer

upon request
vrife@djinn-ai.co
www.djinn-ai.co

Work Experience

Sep 2024 - Present

Djinn AI LLC

AI/ML Engineer & Consultant

MindMoves LLC

Building a Retrieval-Augmented Generation (RAG) model to generate consistently relevant, ethical, and policy-compliant responses to our clients' users' queries from a vast set of archieved documents.
Spearheaded the creation of a multifaceted benchmarking pipeline for the client's RAG model by developing and delivering a set of notebooks, designed to serve as a performance evaluation step critical to quantifying and ensuring data-driven development.

Proton Solutions LLC

Building a Computer Vision model to aid businesses in monitoring and assessing employee performance.
Designed, developed, and deployed several websites for use by clients ranging from embassy staff, restaurants, and a multitude of other businesses.

Jan 2023 - Apr 2025

ARLIS

Machine Learning Engineer

Built a model to predict the next most likely set of user-activity on a website (in terms of element interactions within its DOM structure) using prior such logs of user activity.
Built and published a paper regarding a variation of BERT to predict the "Big-5" personality trait scores and facets of the authors of various essays, social-media posts, and other textual data.
Built and delivered a model to predict the Schwartz value scores of the authors of various extensive multilingual textual data documents.
Built a Python script package to pinpoint and extract linguistic features from text in the Russian language for further translation, data engineering, or model training purposes.
Built and deployed a Computer Vision model to identify and optionally anonymize sensitive information after ingesting PDF, DOCX, or other textual file formats within a DoD working environment enclave (JWICS, NIPR, etc).
Conducted a thorough literature review on the most promising applications of quantum computing in the geospatial information space, selected the most viable approach, and delivered a QCNN model replicating the study’s results for further use by the client.
Built and delivered a standalone testing infrastructure to run a variety of algorithm solvers on classical and quantum chips prior to their delivery and deployment to the client.
Built and deployed an integrated pipeline infrastructure to generate a multitude of metrics and plots to benchmark the performance of classical and quantum chips while active and in use.
Built a Python script package for the multilingual machine recognition, anonymization, filtration, and translation of various textual entities of interest.
Laid the groundwork for a speech recognition and classification model for the purpose of speedily detecting and informing agency staff of distressed on-duty personnel to immediately react in the provision of assistance to their mission.
Laid the groundwork for a dashboard made to streamline internal operations, identify gaps in the organization’s capacity to provide services to its clients of interest, and set recruiting/candidate selection criteria, accordingly.
Conducted a literature review on the most promising potential applications of AI in healthcare for veterans, wrote a report regarding the latest most applicable findings yielding the most merit, and delivered it to the client.

Jun 2022 - Jan 2023

Leidos

ML/SW Engineer

Graduate ML/SW Engineer Intern

Built a Computer Vision model to extract information from the clients’ equipment inspection reports relevant to the implementation of an early-warning anomaly detection system.
Built the user interface for the early-warning anomaly detection system in the form of an Elasticsearch dashboard and integrated it into the client’s internal software.

May 2021 - May 2022

University of Maryland

Teaching Assistant

CMSC421 - Introduction to Artificial Intelligence

Hosted scheduled discussion sessions, office hours, and taught students various AI/ML concepts including constraint satisfaction problems, Markov decision processes, Reinforcement Learning, Q-Learning, and Neural Networks among many others.

US Citizen
DoD Security Clearance upon request
All references upon request

About Me

Pragmatic result-oriented and amicable Machine Learning, and Software Engineer with extensive experience in developing and deploying high-quality AI-powered solutions across a diverse set of industries and data types.

Education

Master of Science - Machine Learning

University of Maryland, College Park

2022 - 2023
Bachelor of Science - Computer Science

University of Maryland, College Park

2019 - 2022

Projects

Geo-Djinn

All-in-one geopolitical visual tool created to simplify the comprehension of complex present-day inter-national and intra-national affairs through the simple click of a button.

Cryo-Djinn

A program utilizing cutting-edge computer vision algorithms to detect and classify pack ice in Arctic and Antarctic shipping lanes, using regularly updated satelite data.