Computer Vision Specialist Job in Dataeaze

job details:

Roles and responsibilities

• Code, train, evaluate and deploy machine learning models that integrate with the complete software solution.

Qualifications

• B Tech in Computer Science / Information Technology
• M Tech / PhD specialization in computer vision

Skills

• Candidate must be good at programming and be able to adapt to any of the basic programming languages like C, C++, Python, Matlab, R, Julia, Java, Go, Rust etc.
• Candidate must have mastery of basic computer science concepts like data structures, algorithms, databases, relational algebra (SQL), operating systems, computer architecture, computer networks.
• Candidate must be comfortable in programming on GNU/Linux in a high performance computing (HPC) setups like multicores, clusters, GPUs, etc.
• Candidate must be able to grasp concepts from latest research papers and implement them in a short time.
• Candidate must have a specialization in AI / ML and should have mastery over the topics in the prerequisites section.
• Candidate must be familiar with ML programming frameworks and libraries and should be able to quickly learn and adapt to the newly emerging ones.
• Candidate must be familiar with computer vision libraries, frameworks, toolboxes and should be able to quickly learn and adapt to the emerging ones.

Prerequisites

Techniques

A) Computer Vision

B) Deep learning for computer vision

Pre-requisites for Machine Learning Engineer.

• Following certifications will be preferred
  • Introduction to Computer Vision, Udacity | Georgia Tech CS 6476 | Prof. Aaron Bobick, Prof Irfan Essa, Arpan Chakraborty
  • Swayam | Deep Learning for Computer Vision By Prof. Vineeth N Balasubramanian | IIT Hyderabad
  • CVIT Summer School series | IIIT Hyderabad

Tools

A computer vision specialist needs to be proficient in different aspects of computer science and engineering. Some of the tools to be familiar with include:

• Data Management
  • Python, Julia, R, jupyter, Pandas, PySpark, numpy, matplotlib, seaborn, streamlit, Kafka
• Core Computer Science
  • C, C++, Python,Java, Scala, NetworkX, igraph, MySQL, PostgreSQL, Linux, Mac, Windows
• Machine Learning
  • PyTorch, Tensorflow, Keras, scikit-learn, XGBoost, LightGBM
• Artificial Intelligence
  • OpenCV, dlib. scikit-image, nltk, SpaCy, faiss, flann, kaldi, sphinx, librosa
• Systems / Computing
  • OpenMP, MPI, Spark, CUDA, AWS, GCloud, Azure, Mosquitto, Paho, Jetson Nano
• Software Engineering
  • Docker, Git, JIRA, Trello, MLOps toolkits