Machine learning Team Leader – Egypt – Information Technology Company – ML-154
Home / Job / Machine learning Team Leader – Egypt – Information Technology Company – ML-154
Information Technology Company located in Cairo, Egypt looking for Machine learning Team Leader with the below requirements:
Bachelor Degree in Mathematics, Statistics, Computer Science, Physics, or in an Engineering or Sciences discipline or related degree
At least 4 years experience in analytics, data science, ML Engineering, or software engineering- or, a Masters’s degree in one of the above-mentioned fields and 2 years of relevant/scientific experience.
At least 1 year of experience leading, mentoring and developing either Machine Learning, Data Science, or Analytics practitioners.
Strong understanding of Supervised machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, Logistic Regression, also Ensembling methods like Gboost, XGboost, LightGboost, and Yandex Catboost with the ability to use Stacking methods between them.
Strong understanding of Unsupervised machine learning techniques and algorithms, such as K-means, DBSCAN, OPTICS, GMM and spectral clustering with the ability to evaluate models using different techniques.
Good knowledge of using Reinforcement Learning algorithms like Q-Learning and Deep Q-learning, SARSA, and Montecarlo methods.
Solid understanding of Deep learning techniques and algorithms, such as MLP, CNN, LSTM, and auto-encoder techniques with the ability to use pre-trained models in CNN like Resnet50, VGG19, Exception, in addition to using state of the art object segmentation and localization algorithms like SSD, YOLO, R-CNN, and faster R-CNN, also have the ability to use GANs as a generator model.
Have a good knowledge of dealing with NLP problems like sentiment analysis, machine translation Named Entity Recognition, Part of Speech Tagging and Language models, also has a good knowledge using embedding methods starting from BOW, TF-IDF, Word2Vec, Glove, FastText, Elmo, and seq2seq models with attention mechanism, also familiar with Transformer based algorithms like BERT, Albert, GPT-2.
For Speech and ASR, have a good understanding of signals, FFT, spectrogram analysis, MFCC, CTC loss, Phonemes, Graphemes, GMM, HMM for Acoustic Model, also can deal with Language Models like KenLim and SRILM, in addition, can deal with speech frameworks like Kaldi, DeepSpeech and Jasper also can use Unicode to roman translation like Buckwalter.
Have a good knowledge of Statistics and Probability.
Data Visualization, Info-Graphics, Excel, pandas, Seaborn.
Working with large data and tools for data analysis, e.g., Pandas, Numpy, Seaborn, matplot, etc.
Experience with AI cloud services providers like MS Azure, Google Cloud, IBM Watson.
Understanding of distributed systems, Multi-GPU processing, and concurrent programming.
The ability to deal with machine learning libraries like Scikit-Learn, TensorFlow, Keras, PyTorch.
Data Cleaning, normalizing, labeling, and algorithms evaluation experience
Have the ability to work with Git, Linux, Docker, and containers clustering and orchestration frameworks like Jenkins, Kubernetes, familiar with CI/CD techniques.
Have the ability to build and deploy models on the edges using Optimized-Based Engines like Tensorflow-Lite and Intel OpenVino.
Has the ability to packaging and deploy models as API using Flask, WSGI, Nginx, or falcon and deploy it on-cloud (SaaS-based software).
Selecting features, building, and optimizing classifiers using machine/deep learning techniques using state-of-the-art techniques.
Object-Oriented Programming (OOP) and software design skills, can transform code to C++. Extensive Python experience would be a plus as would be experienced with Reactive Programming
Familiarity with Time-Series analysis using Hidden Markov Model (HMM) and Deep Learning (LSTM).
Familiarity with Linux/UNIX operating systems, including command-line.
Experience with Agile tools, Jira, Trello, Pivotal Tracker, or related
Experience with ML tools: Keras, Jupyter Notebooks, Pandas, sci-kit-learn, Flask, OpenCV, Tesseract, Numpy, or similar
Able to communicate technical issues with technical & non-technical stakeholders
Preferred Skills/Experience Nice to Have:
Graduate degree in a mathematical, scientific, or engineering discipline
Past involvement or exposure to authoring research papers, findings reports, or conference proceedings
Strong mathematics and data analysis skills
Solid understanding of data types, structures, and algorithms
Understanding of Continuous integration, testing, deployment & release methodologies
Version control such as GIT, Subversion, Team Foundation
Ability to understand large scale software & system architecture
Collaborate with team members to deliver ML and RPA solutions including but not limited to data analytics and analysis, ML model training, and RPA implementation
Identify machine learning architectures and models to solve complex data problems
Work with multiple stakeholders to deliver automated workflows in a timely fashion
Use software development programs and operating systems for development
Define new techniques and best practices for all areas of req and ML
Provide feedback to product and development teams to improve our in house tools
Document process, procedures, and training materials for staff and stakeholders
Attend daily stand-up and periodic team meetings
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