Data Engineering

C++
Python
Understanding of fundamental algorithms (sorting, binary search, statistics etc.) and data structures (array, linked list, stack, queue, tree, heap, hash table, graph) in computer science
Knowledge of object-oriented programming principles (encapsulation, inheritance, polymorphism, SOLID principles)
Knowledge of common signal processing and filtering algorithms (FFT, bandpass filter, median filter, smoothing etc.)
Expertise in optimization/improvement of algorithms performance
Expertise in parallelizing of computational algorithms (Python multiprocessing, C/C++ multi-threading)
Expertise in distributed parallel computation frameworks (e.g. PySpark)
Experience in embedding Python programs to C/C++ code
Understanding of Python object serialization (pickle files)
English: B2 Upper-Intermediate

Bachelor’s degree in Computer Science, a related technical field involving
software/systems engineering, or equivalent practical experience

At least 2 years of work or commercial experience in Machine Learning or Artificial
Intelligence

At least 1 year of work experience using one or more general-purpose programming
languages (for example, Java, C/C++, Python, or Ruby)

5-10+ years of experience researching and developing Machine Learning algorithms
Deep understanding of Machine Learning & Deep Learning concepts and algorithms
Curiosity, empathy, strong research skills and ideas generation mindset.
Ability to do quick prototypes and implement new ideas, finding simple and accurate problem solutions.
Experience with libraries and frameworks (Scikit-learn, TensorFlow, Keras, PyTorch, XGBoost, Catboost, etc.)
Degree in Computer Science, Data Science, Mathematics or similar field

• Knowledge of basics concepts from linear algebra, analytic geometry, matrix decompositions, vector calculus, probability and distribution, continuous optimization.
• Knowledge of algorithms and data structures.
• Knowledge of the mathematical foundations behind machine learning algorithms.
• Advanced python programming and knowledge of libraries: pandas, numpy, scipy, sklearn, xgboost, keras, etc.
• Experience in solving real machine learning problems.
• Experience in developing applications that uses BigData concept (Spark), preferably.

• 3+ years of experience in Data Science.
• Knowledge and hands-on experience with Python, scikit-learn, PySpark.
• Will be a big plus previous MarTech experience — user behavior prediction, recommenders engine, user clustering, dynamic pricing.
• BigData knowledge — data preprocessing and model training on distributed environment.
• Be a creative and self-directed person that can generate meaningful business hypothesis and handle it through a full CRISP-DM cycle.

-Have a PhD or Masters in Computer Vision, Computer Science, or related field.
-Be passionate about creating innovative techniques, and making them robust and scalable.
-Have wide experience in state-of-the-art Computer Vision, DeepLearning, and Pattern Recognition fields.
-Be autonomous, a team-player with a positive mindset.
-Be creative and innovation-focused.
-Excellent English level both written and spoken and ability to effectively communicate complex technical concepts.
-Expertise in at least one area of Computer Vision or Deep Learning (e.g., deep convolutional neural networks, object detection, tracking,
segmentation, image and video processing, graphics rendering)
-Solid programming skills with Python and/or C/C++
-Familiar with Tensorflow

— 2+ years of professional experience in Machine Learning, Computer vision;
— Strong Python knowledge;
— Experience with at least one framework from the list: TensorFlow, PyTorch, Keras;
— Understanding state-of-the-art CV approaches for problems like object detection/tracking, video analysis, semantic segmentation, etc.;
— Experience with some of the well-known neural networks architectures such as Yolo, MobileNet, U-Net, etc.;
— Experience with ML/CV libraries: Opencv, Numpy, Matplotlib, Pandas, etc.;
— GIT;
— At least intermediate level of English.

• Has at least two years as an ML developer
• Strong understanding of machine learning concepts and algorithms: to be familiar with the process (data collection, training, evaluation, and making iterative improvements) of building effective learning systems;
• Practical experience in at least one of the following problems: object detection, segmentation, translations, image processing, classification;
• Experience with data cleaning, analysis, and developing efficient, accurate data annotation schemes.
• Mathematical and/or Algorithmic background (understanding vector math (addition, subtraction), DBSCAN algorithm)
• Knowledge of Python and relevant libs such as Numpy; Opencv-python; Dash; Pymysql; Matplotlib, etc
• Knowledge of Database
  Mongo and MariaDB
• Experience with SQL
• Intermediate and higher English level
• Experience in working with GIT
  JavaScript
  Bash
  Node/Express

— 3+ year commercial experience with hands-on Python development and NLP
— Solid practical and theoretical knowledge of Statistics, Machine Learning and Deep Learning
— Theoretical understanding, practical implementation of classical NLP and Neutral Network driven NLP
— Familiarity with cloud ML Platforms is a plus.
— Experience with DNN frameworks as PyTorch, or TensorFlow
— Upper-Intermediate + English level

• Hands-on experience (3-6 years) developing machine learning solutions with Python for Unstructured Text Based Problems (NLP), including: ML problem analysis, data preparation (Exploratory Data Analysis) & transformation, feature analysis & selection, topic modelling & NER (Named Entity Recognition), ML model selection using parameter tuning, model result analysis and presentation, transfer learning, and developing custom ML models based on requirements
• Excellent knowledge of Python + Java or C++
• Knowledge of PyTorch/TensorFlow/Sagemaker/Docker/MLflow/Kubeflow/Linux, as well as knowledge in the latest neural networks (Transformers, LSTM, GAN, etc.)
• Good knowledge of machine learning libraries (like Scikit-learn, NLTK, spacy, etc.)
• Strong programming knowledge of Python, Flask, NumPy, Pandas, etc.
• Good knowledge of statistics and algorithms
• Experience in image recognition or OCR technology