Freelancers using Python in GatineauFreelancers using Python in Gatineau
Full Stack Mobile & Web | UI/UX Product Engineer | Devops
$25k+
Earned
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Full Stack Mobile & Web | UI/UX Product Engineer | Devops
Product Designer for AI & Digital Products
18
Followers
Product Designer for AI & Digital Products
Cover image for Autonomous AI Career Intelligence Platform
Overview
I
Autonomous AI Career Intelligence Platform Overview I developed an autonomous AI-powered platform designed to automate the job discovery and evaluation process. The system continuously analyzes job opportunities against a candidate profile and delivers ranked recommendations directly through Telegram. Rather than relying on manual job searches, the platform transforms fragmented opportunities into actionable career intelligence. ⸻ The Challenge Job seekers often spend significant time reviewing opportunities that are poorly aligned with their qualifications, experience, or career goals. The objective was to create a system capable of: Monitoring opportunities continuously Evaluating candidate-job fit automatically Ranking opportunities by relevance Delivering personalized recommendations in real time ⸻ Solution Intelligence Layer Developed a scoring engine that evaluates: Technical skills alignment Professional experience relevance Industry compatibility Education requirements Soft skills fit Each opportunity receives a weighted score and detailed evaluation breakdown. ⸻ Recommendation Layer Beyond numerical scoring, the platform generates contextual insights explaining: Why a role is a strong match Which qualifications are missing Potential competitive advantages Areas for improvement This transforms raw job data into actionable decision support. ⸻ Infrastructure The platform operates as an autonomous workflow deployed on Render. Key capabilities include: Automated opportunity monitoring Data processing pipelines AI-driven evaluation Telegram notification delivery Continuous 24/7 execution ⸻ Operational Workflow Candidate submits CV System extracts and analyzes profile information Opportunities are collected and processed Matching engine evaluates compatibility Ranked recommendations are delivered automatically AI-generated insights explain each result ⸻ Key Features ✅ Automated CV Analysis ✅ AI-Powered Matching Engine ✅ Explainable Scoring System ✅ Real-Time Job Monitoring ✅ Telegram-Based Delivery ✅ Continuous Cloud Deployment ⸻ Outcome This project demonstrates my ability to design and deploy production-ready AI workflows that bridge the gap between complex technical systems and real-world efficiency. The result is an autonomous platform that reduces manual effort while improving the quality and relevance of career opportunities presented to the user.
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Cover image for Contra Community Post
Day 17/30: COMMON
Contra Community Post Day 17/30: COMMON ROOM What if a library card could reveal belonging instead of simply proving access? I built COMMON ROOM, a speculative membership system for the fictional North Quarter Public Library. Instead of asking members to choose an identity or complete a personality quiz, the system lets their actual behavior inside the library leave the evidence. Read in the Stacks → leave a margin. Make in the Workshop → leave a registration mark. Follow a question through the Index → leave a reference path. Explore the Quarter → leave a civic trace. Those traces gradually build a unique Member Record. The card remembers in layers. Its physical Accession Aperture later becomes a lens into hidden library memory, and completed cards can optionally become part of a Living Collection that begins to reveal the shape of the neighborhood itself. The project eventually became a system about: BEHAVIOR → EVIDENCE → OBJECT → MEMORY → COMMUNITY And the line that defined the whole thing: You don’t receive a card. You accumulate one. I also built the launch film around the same visual logic instead of doing a traditional product walkthrough using the card’s traces, layers and aperture as the motion language. Would love feedback on one thing in particular: Does the relationship between behavior, the physical card, and belonging read clearly without needing the concept explained first? Day 17 of my 30 Days of Real Business Problems challenge. #ProductDesign #InteractionDesign #CreativeDevelopment #DesignEngineering #MotionDesign #CreativeCoding #ThreeJS #Remotion
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AI/ML | Backend Software Engineer
AI/ML | Backend Software Engineer
Professional software engineer help a business scale 73% up
Professional software engineer help a business scale 73% up
Results-Driven Software Engineer 💻
Results-Driven Software Engineer 💻
Experienced AI Developer
Experienced AI Developer