Hire the Best Julia Developers

11 years building ML systems. PhD in Deep Learning for Document Analysis. Worked with Huawei, Repsol, Kantar Media. I deliver: LLM/VLM integrations (OpenAI, Claude, Gemini APIs) Computer vision pipelines (detection, classification, OCR) Full-stack AI apps (Django, FastAPI, React) RAG systems and document processing Workflow automation and API integrations I've published in top pattern recognition conferences and shipped production systems at scale. I write clean code, communicate clearly, and hit deadlines. Recent freelance work: NLP pipelines, fake review detection, document AI. Find me in linkedin at mcarbonellnunez

I operate at the intersection of 𝐩𝐫𝐨𝐝𝐮𝐜𝐭, 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐥𝐞𝐚𝐝𝐞𝐫𝐬𝐡𝐢𝐩, 𝐚𝐧𝐝 𝐡𝐚𝐧𝐝𝐬-𝐨𝐧 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞/𝐌𝐋 implementation. I help startups and scaleups define technical strategy, build roadmaps, staff and organize engineering teams, and personally implement the core backend and ML components when needed from system design and architecture to model deployment and observability. 𝐖𝐡𝐚𝐭 𝐈 𝐝𝐨: - 𝑪𝑻𝑶 𝒂𝒅𝒗𝒊𝒔𝒐𝒓𝒚 + 𝒉𝒂𝒏𝒅𝒔-𝒐𝒏 𝒊𝒎𝒑𝒍𝒆𝒎𝒆𝒏𝒕𝒂𝒕𝒊𝒐𝒏: architecture, hiring, vendor selection, proof-of-concept → production. - 𝑬𝒏𝒅-𝒕𝒐-𝒆𝒏𝒅 𝑨𝑰 𝒅𝒆𝒍𝒊𝒗𝒆𝒓𝒚: data strategy, model development, MLOps, A/B testing, feature flags. - 𝑫𝒆𝒍𝒊𝒗𝒆𝒓𝒚 & 𝒕𝒆𝒂𝒎 𝒐𝒑𝒔: Agile coaching, sprint governance, capacity planning, risk mitigation. - 𝑺𝒄𝒂𝒍𝒂𝒃𝒊𝒍𝒊𝒕𝒚 & 𝒓𝒆𝒍𝒊𝒂𝒃𝒊𝒍𝒊𝒕𝒚: Micro-services, event-driven architectures, caching, async workers, observability. 𝐓𝐞𝐜𝐡 & 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐒𝐭𝐚𝐜𝐤: Python, FastAPI, Django, PyTorch, TensorFlow, Hugging Face, MLflow, Airflow, Docker, Kubernetes, Terraform, AWS/GCP, Postgres, Redis, Kafka, Prometheus, Grafana, GitHub Actions, Jira, Confluence, Figma. 𝐀𝐜𝐡𝐢𝐞𝐯𝐞𝐦𝐞𝐧𝐭𝐬: - As acting CTO, 𝐝𝐞𝐟𝐢𝐧𝐞𝐝 𝐩𝐫𝐨𝐝𝐮𝐜𝐭 𝐫𝐨𝐚𝐝𝐦𝐚𝐩 𝐚𝐧𝐝 𝐥𝐞𝐝 𝐚 𝟏𝟎-𝐦𝐨𝐧𝐭𝐡 delivery that included MLOps pipelines and a production LLM microservice — 𝐫𝐞𝐬𝐮𝐥𝐭𝐢𝐧𝐠 𝐢𝐧 𝟑𝐱 𝐟𝐚𝐬𝐭𝐞𝐫 𝐟𝐞𝐚𝐭𝐮𝐫𝐞 𝐝𝐞𝐥𝐢𝐯𝐞𝐫𝐲 and a 28% boost in user retention. - 𝐇𝐢𝐫𝐞𝐝 𝐚𝐧𝐝 𝐦𝐞𝐧𝐭𝐨𝐫𝐞𝐝 𝐚 𝟕-𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫 𝐌𝐋 + 𝐛𝐚𝐜𝐤𝐞𝐧𝐝 𝐭𝐞𝐚𝐦; standardized deployments with Terraform + EKS and introduced SLOs/SLAs to reduce mean time to recovery by 70%. I thrive in 𝐡𝐲𝐛𝐫𝐢𝐝 𝐫𝐨𝐥𝐞𝐬 𝐰𝐡𝐞𝐫𝐞 𝐭𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐥𝐞𝐚𝐝𝐞𝐫𝐬𝐡𝐢𝐩 𝐦𝐞𝐞𝐭𝐬 𝐡𝐚𝐧𝐝𝐬-𝐨𝐧 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠. If your team needs someone who can own the roadmap, manage delivery, and also roll up their sleeves to build backend services or AI systems, I’m the right fit. 𝐏𝐨𝐫𝐭𝐮𝐠𝐚𝐥-𝐛𝐚𝐬𝐞𝐝, 𝐫𝐞𝐦𝐨𝐭𝐞-𝐫𝐞𝐚𝐝𝐲, and adaptable to global time zones I specialize in helping startups and scaleups go from 0→1 and then scale reliably. Let’s build something impactful together. 𝐊𝐞𝐲𝐰𝐨𝐫𝐝𝐬 𝐟𝐨𝐫 𝐕𝐢𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐲: CTO, Technical Project Manager, Python, ML Engineer, MLOps, Backend, FastAPI, Django, PyTorch, TensorFlow, Hugging Face, Docker, Kubernetes, Terraform, AWS, GCP, Microservices, Observability, Agile, Scrum, SRE, CI/CD.

I design and deploy production-grade AI systems: from data pipelines to scalable LLM applications. With 7+ years in ML/AI, I specialize in LLM systems, RAG architectures, and MLOps, helping teams move from prototype to reliable, scalable AI in production. My focus is not just building models but ensuring they perform under real-world constraints: latency, cost, hallucination control, and continuous improvement. What I build -End-to-end ML pipelines: ingestion, training, deployment, monitoring -RAG systems with proper evaluation harnesses (retrieval quality, regression catching) -LLM observability: prompt versioning, tracing, feedback loops -Scalable inference (real-time and batch) with GPU optimization -CI/CD for ML with MLflow, Airflow, automated retraining -AI agents with guardrails and reliable tool use Selected results -Fraud detection pipeline (real-time inference) → ~$890K in losses prevented -Forecasting system using ensemble models → 31% accuracy lift over baseline -Multiple LLM products running in production under client SLAs -$3M+ in measurable business impact across deployments (happy to walk through specifics on a call) Stack -Languages/frameworks: Python, FastAPI -LLMs: OpenAI, Anthropic, HuggingFace, LangChain, LlamaIndex -Vector DBs: Pinecone, Weaviate, ChromaDB, FAISS -Infra: AWS, Docker, Supabase, MLflow, Airflow How I work -Replies in 0–4 hours on business days -Production-grade code with tests and docs, not throwaway notebooks -Clear scope, direct communication, focused on business outcomes -Revenue, automation, speed-to-market — that's the scoreboard Let's turn your AI idea into a working product. Send an invite with your project details and I'll get back to you with a clear plan.

About Me: I’m an AWS-certified Machine Learning Engineer with 4+ years of hands-on experience building and deploying production-grade AI and ML systems. I specialize in Large Language Model (LLM) development, Retrieval-Augmented Generation (RAG) pipelines, and Natural Language Processing (NLP) applications such as classification, summarization, and sentiment analysis. With deep expertise in AWS SageMaker and Bedrock, I help organizations move generative AI projects from proof-of-concept to production, ensuring scalability, compliance, and performance. My focus is on building reliable, maintainable AI solutions that integrate seamlessly into existing business workflows. Currently pursuing my MSc in Computer Science (AI/ML) at Georgia Tech, I combine strong theoretical foundations with proven practical skills to deliver solutions that truly drive business outcomes. Services I Offer: 1. Fine-tuning Large Language Models (LLMs) for domain-specific applications 2. Building end-to-end RAG (Retrieval-Augmented Generation) systems with vector databases (Pinecone, Bedrock KB, Opensearch ) 3. Developing AI Agents for intelligent automation and knowledge retrieval 4. Designing and deploying NLP solutions – classification, summarization, sentiment analysis, entity extraction 5. Prompt engineering and model optimization for improved performance and accuracy 6. Production ML Systems – CI/CD pipeline automation, model versioning, and continuous monitoring using AWS SageMaker and related services Skills: Programming: Python, PySpark, JavaScript, FastAPI AI/ML: LLM Development (Hugging Face, LangChain, Bedrock), NLP (spaCy, Transformers) Frameworks/Libraries: Scikit-learn, Pandas, NumPy, TensorFlow, PyTorch Cloud: AWS (SageMaker, Bedrock, Lambda, Glue, API Gateway, CloudWatch, S3) Model Lifecycle: MLflow, CI/CD for ML, Model Monitoring Databases: SQL, Pinecone (Vector DB), DynamoDB AI Optimization: Prompt Engineering, Model Fine-Tuning, Quantization Visualization: Tableau, AWS QuickSight Education: 🎓 MSc in Computer Science (AI/ML) – Georgia Institute of Technology, Atlanta, United States. 🎓 MSc in Cloud Computing (Software Engineering) – Munster Technology University, Cork, Ireland 🎓 BEng in Computer Engineering – Federal University of Technology, Owerri, Nigeria. Certifications: ✅ AWS Certified Solutions Architect – Associate ✅ AWS Certified Machine Learning – Specialty ✅ AWS Certified GenAI Developer – Professional (In progress) Industry Experience: AWS Data/ML Engineer @ HiveTekCorp (Dec 2025 - till present) MLOps Engineer @ Veterans United (Sept 2022 - Sept 2023) Data Scientist @ Veterans United (Dec 2020 - Sept 2022)

𝐖𝐢𝐭𝐡 𝐨𝐯𝐞𝐫 𝟐,𝟒𝟎𝟎 𝐡𝐨𝐮𝐫𝐬 𝐥𝐨𝐠𝐠𝐞𝐝, $𝟏𝟎𝐤+ 𝐢𝐧 𝐞𝐚𝐫𝐧𝐢𝐧𝐠𝐬, 𝐓𝐨𝐩 𝐑𝐚𝐭𝐞𝐝 𝐛𝐚𝐝𝐠𝐞 (𝟗𝟓% 𝐉𝐨𝐛 𝐒𝐮𝐜𝐜𝐞𝐬𝐬 𝐒𝐜𝐨𝐫𝐞), 𝐚𝐧𝐝 𝐜𝐥𝐢𝐞𝐧𝐭𝐬 𝐨𝐮𝐭𝐬𝐢𝐝𝐞 𝐔𝐩𝐰𝐨𝐫𝐤. 𝐈 𝐝𝐨𝐧’𝐭 𝐣𝐮𝐬𝐭 "𝐚𝐬𝐬𝐢𝐬𝐭" — 𝐈 𝐦𝐚𝐧𝐚𝐠𝐞. You need an implementation partner who can figure things out without hand-holding. I hold Bachelor's Degree and bridge the gap between technical operations, creative strategy, and executive administration. My value isn't just in doing tasks; it's in my resourcefulness. Whether you need to manage a coaching community, onboard new SaaS clients, or manage CRM, I bring the professional discipline to get it done right. 𝐇𝐨𝐰 𝐈 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 𝐘𝐨𝐮𝐫 𝐆𝐫𝐨𝐰𝐭𝐡: 💻 𝐓𝐞𝐜𝐡-𝐒𝐚𝐯𝐯𝐲 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 & 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 ✓ Community Ops: Experience building and managing communities on Circle.so and Mighty Networks for coaches, ensuring engagement and smooth user experiences. ✓ Tech Liaison: Served as the bridge between non-technical clients and internal developers. I translate client feedback into technical tickets and guide new users through onboarding/product adoption. ✓ CRM & Automation: Certified in Make.com (Foundation & Basics) . I build scenarios to connect apps and reduce manual data entry, although quite new I'm actively enhancing my skills to meet expectations. I also optimize pipelines in Zoho CRM, Trello, Jira and Monday.com. ⚙️ 𝐄𝐱𝐞𝐜𝐮𝐭𝐢𝐯𝐞 & 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐀𝐝𝐦𝐢𝐧 ✓ Business Discipline: My degree and Civil Service Eligibility provide the foundation for handling your data, confidentiality, and compliance with professional rigor. ✓ Procurement & Logistics: Managed end-to-end procurement cycles, responding to government RFQs and handling strict documentation for US enterprise. ✓ Executive Gatekeeping: Skilled in complex calendar management and acting as the primary point of contact for high-level stakeholders. 🎨 𝐀𝐈-𝐏𝐨𝐰𝐞𝐫𝐞𝐝 𝐂𝐫𝐞𝐚𝐭𝐢𝐯𝐞 & 𝐂𝐨𝐧𝐭𝐞𝐧𝐭 ✓ Visual Assets: Expert in generating consistent character art and marketing visuals using Midjourney, Canva and Photoshop. ✓ Content Scale: I leverage AI to increase content production speed by 2x without sacrificing quality, utilizing prompts and Notion for strategy. ✓ Digital Strategy: Certified in Google Foundations of Digital Marketing & E-commerce. 𝐓𝐞𝐜𝐡 𝐒𝐭𝐚𝐜𝐤: ✓ Community: Circle.so, Mighty Networks, Discord, Telegram, Meta Platforms ✓ Ops/CRM: Monday.com, Zoho CRM, Jira, Trello, Slack, Notion ✓ Creative: Midjourney, Adobe Photoshop, Canva ✓ Automation: Integration and AI Tools Ready for a partner who is resourceful, organized, and tech-forward? Click "𝐈𝐧𝐯𝐢𝐭𝐞 𝐭𝐨 𝐉𝐨𝐛" to discuss your needs.

I build RAG pipelines and LLM-powered applications that actually ship. My recent work includes a production-grade hybrid retrieval system (BM25 + FAISS + Ollama) deployed for a logistics company, significantly reducing their document lookup time across a large knowledge base. Here's what I typically build for clients: — Multi-agent systems using LangGraph and LangChain, handling complex, multi-step reasoning and task orchestration — RAG pipelines with hybrid retrieval (dense + sparse), local LLMs via Ollama, and vector stores like ChromaDB and FAISS — Computer Vision applications for object detection, classification, and domain-specific analysis — AI-powered web apps with React or Next.js frontends and Flask/Python backends — Workflow automation connecting LLMs to external APIs, tools, and data sources via N8N or custom integration I care about systems that are maintainable, explainable, and ready for real users — not just ones that pass a demo. 100% Job Success · Top Rated on Upwork BSc Computer Science — PUCIT CS50's Introduction to AI with Python (HarvardX) · Python for Data Science (Udemy)