Alexa Translations provides A.I.-powered translations for the largest and mostprestigious legal, financial, and government institutions. Our unique combinationof advanced technology and professionally certified translators deliver tailoredsolutions with unparalleled quality. Thanks to over two decades of award-winningclient success, you can rely on us as a true extension of your team.

Developed a model for detecting company names using NLP with an accuracy of 99% on real-world data.Developed a model for clustering search strings and summarizing the result in PDF format using Python (auto reporting) .Hands-on Experience with Large Language Models, and Transformers Agent wrappers to facilitate the integration of LLMs (Large Language Models) such as: OpenAI, HuggingFace, prompt engineering, few-shot and zero-shot learning.Hands-on Experience in Deep Learning, Semantic Textual Similarity, Multi-Class, Multi-Label Classification, Named-Entity Recognition, Multi Documents Summarization, Entity Resolution, Sentiment Analysis, Topic Modeling (text with any length), fine-tuning LLMs and RAG.Hands-on Experience in Deploying Machine Learning in Production & at Scale (AWS MLOPs), EC2, and CI/CD.Hands-on Experience in Data Engineering Pipelines (Sagemaker Pipeline), SQL, Athena, PyTorch, NLTK, Spacy, python.Hands-on Experience in handling imbalanced data, data cleaning, statistical tests, and agile management.

- Develop a model from lab’s cell data to predict real-life battery pack State of Health (SOH) with 95% accuracy for electric vehicles. - Develop a model from lab’s cell data to predict the Remaining Useful Life (RUL) of cells with 91% accuracy (after 20% of lifetime) for electric vehicles. - Develop a model for fault detection in battery packs with 100% accuracy after 5 cycles on simulation data. - Hands-on Experience in data cleaning, feature engineering, deep learning, regression, time series, anomaly detection. - Hands-on Experience in research, data analysis, reporting and documentation. - Hands-on Experience in data Engineering Pipeline, handling imbalanced data and Deploying Machine Learning in Production (MLOPs). - Hands-on Experience in python, TensorFlow, sklearn, statistical tests, simulation and Matlab.

- Developing a model for classifying brain wave signals (EEG signals) with 85% accuracy using FBCSP(Filter bank common spatial pattern) method. - This model was used to improve an Alzheimer cognitive enabler model for helping people with Alzheimer to detect familiar people from non-familiar people. (United Therapeutics Corporation) with 87% accuracy. - Hands-on Experience in python and sklearn. - Hands-on Experience in research, data cleaning, feature engineering, machine learning, binary and multi class classification.

Develop models for predicting stocks and a model for predicting volatility surface parameters, and a tool for portfolio creation.Develop tools for option creation (ATM, OTM, ITM) and stop loss and take profit calculation.Writing back test code for checking the model’s performance and production engine for predicting stocks movements.Hands-on Experience in Deploying Machine Learning in Production and at Scale (AWS MLOPs) and CI/CD.Hands-on Experience in time series analysis, regression, and classification.Hands-on Experience in data analysis, statistical tests, reporting and documentation, and agile management.Hands-on Experience in Data Engineering Pipelines, SQL, PostgreSQL, AWS, EC2 S3.Hands-on Experience in python, TensorFlow, PyTorch and sklearn.

- Wrote and published multiple peer-reviewed articles in high-impact factor journals including nature publishing group with high citations (All first author). - Won a strategic research grant for machine learning-assisted plasmonic nanostructures design funded by National Research Foundation and best poster award in an international conference. - Hands-on Experience in research, data analysis, data augmentation, reporting, documentation, simulation, Matlab and Comsol. - Hands-on Experience in Resnet architecture, DQNN and rainbow. - Hands-on Experience in CNN, RNN, image processing, computer vision, reinforcement learning and regression. - Hands-on Experience in python, TensorFlow, PyTorch and sklearn.

- Wrote and published multiple peer-reviewed articles in high-impact factor journals including nature publishing group with high citations (All first author). - Won a strategic research grant for machine learning-assisted plasmonic nanostructures design funded by National Research Foundation and best poster award in an international conference. - Hands-on Experience in research, data analysis, data augmentation, reporting, documentation, simulation, Matlab and Comsol. - Hands-on Experience in Resnet architecture, DQNN and rainbow. - Hands-on Experience in CNN, RNN, image processing, computer vision, reinforcement learning and regression. - Hands-on Experience in python, TensorFlow, PyTorch and sklearn.

Supervised the manufacturing of Optical fiber, power and telecommunication cables from the raw materials to delivering to customers.Managed over 30 people on different levels.Developed and analyzed quality control processes and deliverables to determine present standards and establish recommended action plans.Collaborated with development teams, internal customers, and product line management to verify delivery of desired quality requirements to distributors.Experience in Quality Management, quality audits and inspections, Establishing quality standards and procedures, ISO 9001.Experience in Process Improvement, continuous improvement initiatives, Implementing corrective and preventive actions.Experience in Testing and Inspection, Developing quality testing protocols, product inspections and evaluations, Ensuring compliance with industry standards and regulations.Experience in data analysis, statistical tests, quality data, and metrics, Generating reports, Microsoft Office.Experience in Problem-solving, Team Leadership, Communication, customer facing, Regulatory Compliance, Documentation, Attention to Details, Team management, and agile management.