Deep Learning

— Technologies:
Mediapipe framework (Skeleton models and behavior recognition)
yolov5
CNNs
Torch
Python
OpenCV
Experience with models on edge devices

— Experience:
2+ years in CV applications;
previous experience in building high load computer vision applications;
previous experience in training and deploying of light models on EDGE device;
models distillation.

• Experience in commercial development in Rust
• Experience in participating in open-source projects
• Experience in managing a development team
• Strong English communication and presentation skills

● Python experience
● Prior experience with machine learning or computer vision is a big plus, but may not be strictly necessary if you are able to learn fast and understand relevant technical documentation.

-3+ years (middle) and 5+ years (senior) of successful data science experience
-Experience with/good knowledge of NLP, pattern recognition, deep learning and other ML technologies
-Excellent programming skills, expert in Python
 - Strong experience with Tensorflow / PyTorch / Keras
-Degree in Math / Statistics / Physics

• Preferred: experience with big data processing technology stack (Spark, Hadoop, etc.)
  -A sense of urgency and ownership over the product
  -Proactive, high-energy, competitive, and creative individual
  -Driven to outperform; dedicated to self-improvement
  -Experience in a remote SCRUM team involving daily meetings, grooming, planning, etc
  -English level: Intermediate or higher

• hands-on experience with developing, evaluating, and releasing computer vision algorithms into production software;
• 2+ years of experience in developing novel computer vision algorithms or similar methods based on deep learning in such topics as image recognition, geometric deep learning, object recognition using 3D spatial data
• passionate about what you do and enjoy working in a collaborative environment
• upper-intermediate+ verbal and written English level.

• A minimum of a Bachelor’s degree in a mathematical discipline such as Computer Science, Applied Statistics, Maths, Engineering, or Physics from a respected University. A Ph.D. is a bonus
• 4+ years experience in Python and good knowledge of R
• At least 4 years practical experience of univariate and multivariate statistical analysis in Python or R with large data sets (millions of records and many tens or hundreds of independent variables)
• Good experience of variable transformation and data preprocessing techniques to extract maximum predictive power such as binning, piecewise linear regression, non-linear function transforms, etc.
• Excellent practical knowledge of multi-variate techniques such as Logistic Regression, Decision Trees, Random Forest, Naive Bayes, Clustering, etc. and a good grasp of the strengths and weaknesses of specific approaches
• Strong communication skills

Ability to write code in Python.
Strong algorithmic skills.
Basic knowledge and practical experience of Machine Learning.
Knowledge of Machine Learning-related math (linear algebra, probability theory, etc.).
Basic knowledge of software architecture design.
Active involvement and interest in Machine Learning.
Experience with some Machine Learning-related libraries, such as NumPy, Matplotlib, NLTK, Pandas, SkiPy and others.
Communication skills.

● 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, Developing custom ML Model based on requirement
● Good knowledge of machine learning libraries (like Scikit-learn, NLTK, spacy etc.)
● Strong programming knowledge in Python, Flask, NumPy, Pandas etc.
● Good knowledge in statistics and algorithms
● Experience in image recognition or OCR technology

● Professional data engineering experience focused on batch and real-time data pipelines using Spark, PySpark, Python (Scala is a plus).
● Strong hands-on working experience of Big Data stack including Spark and Python(Pandas is a plus).
● Awareness of DevOps.
● Hands-on design and development experience in data space: data processing/data transformation using ETL tools, a data warehouse (data modeling, programming).
● Exposure to Google Cloud and Amazon Web Services.
● Experience working in a high load / high performance distributed project.
● Experience both with async code and with multithreading/multiprocessing.
● Hands-on experience with SQL (e.g. PostgreSQL) and NoSQL databases (MongoDB, Redis, Elasticsearch, etc.)
● An open-minded person who is willing to work in a dynamic R&D environment.