Where the models were built.Research and production.
From a research lab in Moscow to a startup in New York. Open any card for the detail.
8 roles, newest first
Showing 6 of 8 roles
Current
AI & Product
Mar 2026 — Now
Founder & AI Software Engineer
Afrimoll
Building and running the marketplace platform end to end — the data model, authentication, storage and edge functions behind its vendor, buyer and admin dashboards.
40+vendors onboarded
700+community followers
Own the platform end to end: Supabase/PostgreSQL data model, authentication, storage and edge functions behind vendor, buyer and admin dashboards.
Shipped vendor subscription plans (a free listing tier and paid plans), storefronts, and product and service booking.
Ran A/B tests on plan packaging and onboarding, reading outcomes from event tracking and SQL cohort queries.
Integrated Google sign-in (own Google Cloud OAuth client), email (Brevo), and the Telegram and WhatsApp APIs.
Diagnosed and fixed production failures across row-level security policies, auth configuration, environment variables and gateway timeouts.
Supabase
PostgreSQL
Auth & RLS
API integrations
A/B testing
6 mos
AI & Product
Nov 2025 — Apr 2026
AI Software Engineer (Full-Stack Product Engineer)
Qenfi · Lima, Peru (remote)
Delivered a consumer-credit and device-financing platform from architecture and data model to production launch. The project is now paused.
Owned delivery of a consumer-credit and device-financing platform, from architecture and Supabase/PostgreSQL data model to production launch.
Built admin and super-admin panels for applications, devices and credit operations, and a client portal for loan contracts, payment schedules and device status.
Implemented authentication and role-based access control across the admin, super-admin and client portals.
Fintech
Supabase
PostgreSQL
RBAC
Full-stack
5 mos
AI & Product
Mar 2025 — Jul 2025
AI Specialist
QuestMeUp · Florida, USA
Led AI development for a personalised assessment platform, designing and fine-tuning the models behind its adaptive user journeys.
Designed and fine-tuned AI models for personalised assessments and adaptive user journeys.
Translated technical workflows into clear documentation for a non-specialist team.
Shaped the platform vision and AI roadmap so development stayed aligned to user goals.
LLM fine-tuning
Product
Technical writing
4 mos
AI & Product
Nov 2024 — Feb 2025
AI Engineer
GdeRadost · Moscow, Russia
Improved model response quality on a production assistant through prompt engineering and fine-tuning.
+75%response accuracy
Raised response accuracy of a production AI assistant by 75% through prompt engineering, fine-tuning and systematic evaluation.
Shipped with engineers and analysts across departments.
Wrote evaluation reports and technical memos that informed deployment decisions.
Prompt engineering
Fine-tuning
Evaluation
2 yrs 10 mos
AI & Product
Growth & Partnerships
Mar 2022 — Dec 2024
Founder, CEO & ML Engineer
GT Augment · Abuja, Nigeria
Founded and ran an applied-AI company building education, marketing and augmented-reality products.
$100kfunding secured
1,000+users
3countries
Developed 3 proprietary AI models for education, marketing and AR-based engagement.
Secured $100,000 in funding and scaled across 3 countries to 1,000+ users.
Oversaw technical content, investor decks and platform documentation.
Founder
Applied AI
AR
Fundraising
4 mos
AI & Product
Jun 2024 — Sep 2024
AI Research Intern
Dugree · New York, USA
Research on large language model efficiency, contributing to publications and internal symposiums.
+45%model efficiency
5+publications
Optimised LLMs for a 45% increase in model efficiency.
Contributed to 5+ research publications and presented findings at internal symposiums.
Authored research briefs and experimental documentation for cross-functional review.
LLM optimisation
Research
Publications
Impact
What the models did.Each figure from the role behind it.
Dugree
+45%
model efficiency
LLM optimisation research in New York.
GT Augment
$100k
funding secured
Raised for the applied-AI company he founded and ran.
MIPT
+60%
student performance
From AI-driven educational models at MIPT.
Dugree
5+
publications
Research contributions, presented at internal symposiums.
Case studies
Selected work.Problem, approach, outcome.
Three projects where the constraint was real and the result is measurable.
2024Berom Community in Diaspora
Berom AI
Researcher & Engineer
800k+speakers served
+30%online presence
Problem
Berom is spoken by roughly 800,000 people in central Nigeria and is almost absent from the internet. Low-resource languages like it are invisible to the models that increasingly mediate access to information — which means the language quietly stops being usable in the places people now live.
Approach
Built an NLP model on transformer architectures trained over linguistically enriched Berom datasets, working with the community in diaspora to assemble material that did not previously exist in machine-readable form.
Outcome
Improved accuracy and scalability for low-resource NLP, raised Berom's online presence by 30%, and made the language usable in educational and communicative software for its 800,000+ speakers. The work fed into wider research frameworks on indigenous languages.
Transformers
Hugging Face
PyTorch
Low-resource NLP
2024Ftizisbiomed
Fluorogram Analysis Model
ML Engineer
10,000+images processed
+20%diagnostic precision
Problem
Thoracic abnormalities are missed in routine fluorographic screening, and radiologist time is the bottleneck that makes review at population scale impractical.
Approach
Designed a machine-learning pipeline processing 10,000+ fluorographic images using computer vision techniques, tuned for the failure modes that matter clinically rather than for headline accuracy.
Outcome
A 20% increase in diagnostic precision, presented at Ftizisbiomed's symposium on AI in healthcare.
Computer vision
Python
TensorFlow
Medical imaging
2024Latoken
Latoken AI Assistant
Engineer — hackathon winner
−50%response time
1,000+weekly interactions
Problem
High-volume customer service where response latency, not answer quality, was the thing losing people.
Approach
Engineered a conversational assistant on LLMs with context-aware dialogue management, built for sustained throughput rather than demo conditions.
Outcome
Cut response time by 50% while handling 1,000+ interactions a week. Won the Latoken AI Hackathon. The findings contributed to frameworks for scalable AI-assisted customer engagement.
LLMs
RAG
LangChain
Dialogue management
Tools
Named, not rated.What the work above shipped with.
Machine learning
AI & Product
PyTorch
TensorFlow
Scikit-learn
Hugging Face
Transformers
Weights & Biases
Language models
AI & Product
Fine-tuning
Prompt engineering
RAG
Embeddings
LangChain
LLaMA 3
Engineering
AI & Product
Python
SQL
Docker
Git
Airflow
Languages
Every track
English — Native
Russian — C1 Advanced
Hiring
Open to AI and product roles.
AI specialist, ML engineer and AI product roles — remote or on-site.
