📄 AI-Powered Document Summarizer with RAG and LLMs: Led the development of a robust document summarizer leveraging Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and Natural Language Processing (NLP) techniques. Delivered a scalable and high-accuracy solution for extracting insights from unstructured text data.👥 Team Mentorship and Knowledge Sharing: Reviewed, supported, and mentored team members, fostering collaboration and continuous improvement. Provided… Show more 📄 AI-Powered Document Summarizer with RAG and LLMs: Led the development of a robust document summarizer leveraging Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and Natural Language Processing (NLP) techniques. Delivered a scalable and high-accuracy solution for extracting insights from unstructured text data.👥 Team Mentorship and Knowledge Sharing: Reviewed, supported, and mentored team members, fostering collaboration and continuous improvement. Provided technical guidance to ensure project success and long-term maintainability.📅 Agile Planning and Delivery Management: Planned, groomed, and estimated work for sprints and quarterly roadmaps, ensuring alignment with business goals and timely delivery of milestones.⚙️ Microservices Architecture for Scalability and Cost Efficiency: Reduced operational costs and improved application robustness by implementing microservices, enabling modular development, easier maintenance, and enhanced scalability.🚀 Accelerated Team Performance and Delivery: Improved team delivery timelines and productivity within the first month of leadership, streamlining processes and setting clear priorities to meet deadlines effectively. Show less

🎯 I can help you if you are:• A 𝗳𝘂𝗻𝗱𝗲𝗱 𝘀𝘁𝗮𝗿𝘁𝘂𝗽 looking to scale or optimize ML workflows• A company with an existing ML team that needs 𝘀𝗽𝗲𝗰𝗶𝗮𝗹𝗶𝘇𝗲𝗱 𝗠𝗟𝗢𝗽𝘀 expertise• An organization seeking 𝗰𝗼𝘀𝘁-𝗲𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲, 𝗵𝗶𝗴𝗵-𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 solutions in ML or Big Data👥 Need a 𝗳𝘂𝗹𝗹 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝘁𝗲𝗮𝗺 for your project? Beyond individual expertise, I also offer 𝗼𝘂𝘁𝘀𝗼𝘂𝗿𝗰𝗶𝗻𝗴 𝘀𝗲𝗿𝘃𝗶𝗰𝗲𝘀 with a skilled team… Show more 🎯 I can help you if you are:• A 𝗳𝘂𝗻𝗱𝗲𝗱 𝘀𝘁𝗮𝗿𝘁𝘂𝗽 looking to scale or optimize ML workflows• A company with an existing ML team that needs 𝘀𝗽𝗲𝗰𝗶𝗮𝗹𝗶𝘇𝗲𝗱 𝗠𝗟𝗢𝗽𝘀 expertise• An organization seeking 𝗰𝗼𝘀𝘁-𝗲𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲, 𝗵𝗶𝗴𝗵-𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 solutions in ML or Big Data👥 Need a 𝗳𝘂𝗹𝗹 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝘁𝗲𝗮𝗺 for your project? Beyond individual expertise, I also offer 𝗼𝘂𝘁𝘀𝗼𝘂𝗿𝗰𝗶𝗻𝗴 𝘀𝗲𝗿𝘃𝗶𝗰𝗲𝘀 with a skilled team of up to 5 engineers ready to tackle e2e 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 and 𝗕𝗶𝗴 𝗗𝗮𝘁𝗮 projects. Whether you need dedicated professionals to support your existing staff or a full team to bring your vision to life, we ensure seamless integration with your goals, mission, and timelines.𝗚𝗘𝗧 𝗜𝗡 𝗧𝗢𝗨𝗖𝗛 📧 𝗘𝗺𝗮𝗶𝗹: stefan.micic@brainiac-ml.com🌐 𝐃𝐈𝐒𝐂𝐎𝐕𝐄𝐑 𝐇𝐎𝐖 𝐈 𝐂𝐀𝐍 𝐇𝐄𝐋𝐏 𝐘𝐎𝐔 𝐃𝐄𝐋𝐈𝐕𝐄𝐑 𝐇𝐈𝐆𝐇-𝐐𝐔𝐀𝐋𝐈𝐓𝐘 𝐅𝐄𝐀𝐓𝐔𝐑𝐄𝐒 𝐎𝐍 𝐓𝐈𝐌𝐄: https://bit.ly/StefanMicicPortfolio💬 Send me a 𝗺𝗲𝘀𝘀𝗮𝗴𝗲 on LinkedIn Show less

🚀 Designed Scalable MLOps Pipelines: Built end-to-end MLOps pipelines for multiple clients, enabling seamless data preprocessing, model training, versioning, and deployment. Achieved up to a 4x reduction in model deployment time and improved model retraining efficiency by automating processes.⚙️ Optimized Data Workflows for High-Impact Results: Streamlined ETL processes and data workflows across client projects, resulting in 2x faster data processing times and 50% cost reduction in… Show more 🚀 Designed Scalable MLOps Pipelines: Built end-to-end MLOps pipelines for multiple clients, enabling seamless data preprocessing, model training, versioning, and deployment. Achieved up to a 4x reduction in model deployment time and improved model retraining efficiency by automating processes.⚙️ Optimized Data Workflows for High-Impact Results: Streamlined ETL processes and data workflows across client projects, resulting in 2x faster data processing times and 50% cost reduction in data storage and compute costs through efficient resource allocation and data versioning.📈 Enhanced Model Performance and Reliability: Refined model training and inference processes to increase accuracy and stability. In one project, optimized model architecture and deployment for a 30% boost in model accuracy and a 3x increase in inference speed.🌐 Cross-Industry Expertise in Diverse Team Environments: Successfully delivered solutions for clients in industries such as finance, healthcare, and e-commerce, adapting to team sizes from small startups to large enterprises. Consistently met or exceeded client KPIs, with a 95% client satisfaction rate across projects.📊 Implemented Best Practices in Data and Model Management: Utilized tools like MLFlow, LakeFS, and Docker to ensure reproducibility and scalability, setting up data and model versioning systems that reduced maintenance overhead by 40% and improved collaboration and traceability.If this is interesting to you, feel free to reach out:📧 𝗘𝗺𝗮𝗶𝗹: stefan.micic@brainiac-ml.com🌐 𝐃𝐈𝐒𝐂𝐎𝐕𝐄𝐑 𝐇𝐎𝐖 𝐈 𝐂𝐀𝐍 𝐇𝐄𝐋𝐏 𝐘𝐎𝐔 𝐃𝐄𝐋𝐈𝐕𝐄𝐑 𝐇𝐈𝐆𝐇-𝐐𝐔𝐀𝐋𝐈𝐓𝐘 𝐅𝐄𝐀𝐓𝐔𝐑𝐄𝐒 𝐎𝐍 𝐓𝐈𝐌𝐄: https://bit.ly/StefanMicicPortfolio💬 Send me a 𝗺𝗲𝘀𝘀𝗮𝗴𝗲 on LinkedIn Show less

DISCOVER HOW I CAN HELP YOU DELIVER HIGH-QUALITY FEATURES ON TIME BYCLICKING ON THE LINK BELOW THE BULLET POINTS🌟 Led Architecture Design: Orchestrated the architecture design process, ensuring optimal functionality and scalability for the financial chatbot advisor project.🤝 Client Collaboration: Fostered seamless communication with clients, understanding their needs and objectives to tailor the solution accordingly.🛠️ End-to-End Implementation: Spearheaded the… Show more DISCOVER HOW I CAN HELP YOU DELIVER HIGH-QUALITY FEATURES ON TIME BYCLICKING ON THE LINK BELOW THE BULLET POINTS🌟 Led Architecture Design: Orchestrated the architecture design process, ensuring optimal functionality and scalability for the financial chatbot advisor project.🤝 Client Collaboration: Fostered seamless communication with clients, understanding their needs and objectives to tailor the solution accordingly.🛠️ End-to-End Implementation: Spearheaded the entire implementation lifecycle, from conception to deployment, ensuring a seamless and efficient process.👨‍🏫 Mentorship and Guidance: Provided mentorship and guidance to team members, fostering a collaborative environment and empowering them to excel.💬 Financial Chatbot Advisor: Developed a cutting-edge financial chatbot advisor, leveraging AI and NLP technologies to deliver personalized financial guidance and support to users. Show less

📈 Test Coverage Improvement: Significantly increased test coverage from 5% to 85%, driving better code reliability and performance.🚀 IaC: Used Terraform for setting up DataDog monitoring for observability.🧠 ML Pipelines: Worked with end-to-end pipelines using AWS SageMaker, from data preprocessing and model training to deployment, ensuring seamless operations.📊 Monitoring & Scalability: Utilized Grafana for real-time monitoring and worked with DynamoDB to support… Show more 📈 Test Coverage Improvement: Significantly increased test coverage from 5% to 85%, driving better code reliability and performance.🚀 IaC: Used Terraform for setting up DataDog monitoring for observability.🧠 ML Pipelines: Worked with end-to-end pipelines using AWS SageMaker, from data preprocessing and model training to deployment, ensuring seamless operations.📊 Monitoring & Scalability: Utilized Grafana for real-time monitoring and worked with DynamoDB to support scalable solutions. Show less

🔧 End-to-End Spark & Scikit-Learn Pipeline: Designed and implemented a comprehensive end-to-end pipeline utilizing Apache Spark and Scikit-Learn. This pipeline seamlessly integrates data preprocessing, feature engineering, model training, and evaluation stages, ensuring a streamlined and efficient workflow.🌐 Scalable Data Processing with Apache Spark: Leveraged the power of Apache Spark to handle large-scale data processing tasks, enabling efficient parallel computation and… Show more 🔧 End-to-End Spark & Scikit-Learn Pipeline: Designed and implemented a comprehensive end-to-end pipeline utilizing Apache Spark and Scikit-Learn. This pipeline seamlessly integrates data preprocessing, feature engineering, model training, and evaluation stages, ensuring a streamlined and efficient workflow.🌐 Scalable Data Processing with Apache Spark: Leveraged the power of Apache Spark to handle large-scale data processing tasks, enabling efficient parallel computation and distributed data processing across clusters.📊 Advanced Machine Learning with Scikit-Learn: Utilized Scikit-Learn's robust library of machine learning algorithms and tools to develop predictive models, perform feature selection, and optimize model performance.⚙️ Automation and Efficiency: Implemented automation mechanisms and optimization techniques to enhance the efficiency of the pipeline, reducing manual intervention and maximizing productivity.🚀 End-to-End Solution Delivery: Delivered a fully operational end-to-end solution, empowering stakeholders to extract actionable insights from data and drive informed decision-making. Show less

🌐 Distributed Data Processing with PySpark and AWS: Spearheaded distributed data processing (ETL) and KPI calculations using PySpark and AWS, harnessing the power of distributed computing to efficiently handle large volumes of data.🚀 Leading ELT Project: Led an ELT project aimed at seamlessly transferring data from one source (GraphQL) to another (Azure SQL) and preparing optimized queries for analytics. This involved orchestrating the entire data movement process and ensuring data… Show more 🌐 Distributed Data Processing with PySpark and AWS: Spearheaded distributed data processing (ETL) and KPI calculations using PySpark and AWS, harnessing the power of distributed computing to efficiently handle large volumes of data.🚀 Leading ELT Project: Led an ELT project aimed at seamlessly transferring data from one source (GraphQL) to another (Azure SQL) and preparing optimized queries for analytics. This involved orchestrating the entire data movement process and ensuring data integrity and accuracy throughout.📊 Empowering Analytics with Azure: Deployed the ELT solution using Azure Container Registry, enabling seamless deployment and scaling of containerized applications on the Azure platform. This streamlined approach facilitated efficient data processing and analytics workflows for stakeholders.💡 Driving Insights and Decision-Making: Empowered stakeholders to extract actionable insights from data by providing robust ETL and ELT solutions, paving the way for informed decision-making and strategic initiatives. Show less

🚀 Deep Learning Model Optimization: Leveraged advanced techniques such as ONNX conversion, Quantization, and EC2 instance optimization to optimize already trained Deep Learning models, resulting in a 3x decrease in cost and a 4x increase in throughput.⚙️ Automated Model Evaluation and Deployment: Implemented automated model evaluation and deployment pipelines using AWS services (CloudWatch, SQS, S3, EC2), Valohai, and GitHub Actions. With a streamlined workflow, new code pushes to main… Show more 🚀 Deep Learning Model Optimization: Leveraged advanced techniques such as ONNX conversion, Quantization, and EC2 instance optimization to optimize already trained Deep Learning models, resulting in a 3x decrease in cost and a 4x increase in throughput.⚙️ Automated Model Evaluation and Deployment: Implemented automated model evaluation and deployment pipelines using AWS services (CloudWatch, SQS, S3, EC2), Valohai, and GitHub Actions. With a streamlined workflow, new code pushes to main trigger the deployment of a new model version to staging, facilitating seamless testing and comparison against the current production model.📈 Strategic Decision-Making: Took charge of decision-making and strategic planning for the CI/CD pipeline, including defining the architecture, versioning experiments, and optimizing the ML inference architecture. This proactive approach ensured efficient and effective deployment of models while maintaining high standards of performance and reliability. Show less

📱 Android Model Deployment and Optimization: Led a team of engineers in developing object detection and classification models specifically optimized for Android devices to detect and classify COVID test results. Leveraged techniques such as quantization, TensorFlow Lite, and MobileNet to ensure the model was lightweight and efficient for mobile deployment.🔍 Advanced Super-Resolution R&D: Spearheaded a high-impact R&D initiative to enhance an existing super-resolution model with over… Show more 📱 Android Model Deployment and Optimization: Led a team of engineers in developing object detection and classification models specifically optimized for Android devices to detect and classify COVID test results. Leveraged techniques such as quantization, TensorFlow Lite, and MobileNet to ensure the model was lightweight and efficient for mobile deployment.🔍 Advanced Super-Resolution R&D: Spearheaded a high-impact R&D initiative to enhance an existing super-resolution model with over 95% accuracy. Conducted extensive experimentation with custom loss functions and novel layer designs, implementing these from scratch to boost performance. Introduced innovative techniques, including multi-phase learning and combined loss functions, achieving significant gains in visual fidelity.🧩 ONNX Runtime Integration: Enabled ONNX Runtime to leverage the MIGraphX library, enhancing model support and performance. This integration expanded the library’s compatibility and improved inference efficiency for deep learning workflows.⚙️ ML Compiler Optimization for BERT Models: Identified and addressed performance bottlenecks in BERT-like models by designing custom operators in PyTorch and C++. This involved pinpointing inefficiencies and replacing them with optimized components, significantly improving runtime and resource efficiency in inference tasks. Show less

👁️ Real-Time Object Detection and Classification: Developed high-accuracy YOLO-based models to detect people and assets in real-time video streams, achieving over 97% on all business-critical metrics. Following detection, implemented CNN-based categorization (ResNet with transfer learning) to assess behaviors, such as identifying if a person is sitting or standing.🛠️ MLOps and Deployment: Managed the entire MLOps lifecycle, using MLFlow for model versioning, LakeFS for data… Show more 👁️ Real-Time Object Detection and Classification: Developed high-accuracy YOLO-based models to detect people and assets in real-time video streams, achieving over 97% on all business-critical metrics. Following detection, implemented CNN-based categorization (ResNet with transfer learning) to assess behaviors, such as identifying if a person is sitting or standing.🛠️ MLOps and Deployment: Managed the entire MLOps lifecycle, using MLFlow for model versioning, LakeFS for data versioning, AWS S3 for data storage, and TensorFlow Serving in Docker for scalable deployment. Built a fully automated pipeline that allowed clients to trigger data preprocessing, model training, versioning, and deployment with minimal manual intervention.📊 Automated KPI Calculation for Business Insights: Contributed to multiple projects focused on calculating critical KPIs by implementing robust ETL processes. Leveraged Spark (in both Scala and Python) for data transformations, along with Snowflake, AWS (S3, Lambda, Fargate), and orchestrators like Airflow and Prefect to build scalable and efficient data pipelines that supported business decision-making and analytics. Show less