Biniam Berhe

Background

About Biniam Berhe

Results-driven, Curious, and Creative software engineer with a proven track record of 13+ years of experience in Full Systems Development Life Cycle (SDLC) as a Full Stack Java developer with methodologies like Waterfall and Agile. Implemented from simple to scalable enterprise applications with strong debugging and troubleshooting skills. Great experience with Business Process Management tools like Appian. I have great communication, interpersonal, analytical, and problem-solving skills. Productive and comfortable working in a tight environment. I enjoy giving back to the community by volunteering to teach coding for elementary, middle and high school students. Skills: J2ME, J2EE, JSP, JSF, bootstrap, Struts, JDBC, Servlets, Log4J, JUnit, AJAX, MVC Framework, Spring, Hibernate, iBatis, Apache Tomcat, WebSphere, Glassfish, Eclipse, NetBeans, CVS, SVN, Clear Case, Git/GitHub, Bitbucket, Clear Quest, Apache Maven, Apache Ant, Hudson, Nexus, SOAP Web Service, LDAP, Python, Jupiter notebook, PyCharm CE, Pandas, Numpy, Distributions, Hypothesis testing in Python, Spring Boot, Appian, Angular 2, React. Generative AI Fundamentals Skills: Generative AI Fluency • Image classification • Transfer learning • Training neural networks • Hugging Face • Parameter-Efficient Fine-Tuning • Prompt Engineering • Deep learning • PyTorch • Foundation Models • Ethical AI Large Language Models (LLMs) & Text Generation Skills: Together AI API • Search implementation in Python • NLP transformers • GPT • Selenium • Large Language Models • Data cleaning • Natural language processing • Bert • OpenAI API • Retrieval-Augmented Generation • Transformer neural networks • Prompt Engineering • Pandas • PyTorch • Tokenization • Cosine • API requests • Recurrent neural networks • Attention mechanisms • Text generation • Beautifulsoup • Data quality assessment • Word embeddings • Data scraping Computer Vision and Generative AI Skills: Image pre-processing • Transfer learning • Word embeddings • Ethical AI • Diffusion Models • Yolo algorithm • Model evaluation • Text generation • Computer vision fluency • Image classification • Large Language Models • Pandas • Image generation • Training neural networks • Convolutional neural networks • Parameter-Efficient Fine-Tuning • Image segmentation • Computer Vision Transformers • Tokenization • Data quality assessment • Generative adversarial networks Building Generative AI Solutions Skills: Vectors • Retrieval-Augmented Generation(RAG) • OpenAI API • LangChain