Sr. Machine learning

at  Dezzex

We are looking for a Machine Learning (ML) Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in python, pytorch, tensorflow framework and edge computing and programming. If you have knowledge of data science and software engineering, we’d like to meet you. Your ultimate goal will be to shape and build efficient self-learning applications.

Responsibilities

• Study and transform data science prototypes
• Design machine learning systems
• Research and implement appropriate ML algorithms and tools
• Develop machine learning applications according to requirements
• Select appropriate datasets and data representation methods
• Run machine learning tests and experiments
• Perform statistical analysis and fine-tuning using test results
• Train and retrain systems when necessary
• Extend existing ML libraries and frameworks, python, pytorch, tensorflow framework and edge computing
• Good understanding of ML Pipeline
• Keep abreast of developments in the field
• Skills

*

• Proven experience as a Machine Learning Engineer or similar role
• Understanding of data structures, data modeling and software architecture
• Deep knowledge of math, probability, statistics and algorithms
• Ability to write robust code in Python, jupiter notebook and R
• Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
• Excellent communication skills
• Ability to work in a team
• Outstanding analytical and problem-solving skills
• BSc in Computer Science, Mathematics or similar field; Master’s degree is a plus

Job Type: Full-time
Pay: AED10,000.00 - AED20,000.00 per month

Experience:

• Relevant: 5 years (Required)

• Study and transform data science prototypes
• Design machine learning systems
• Research and implement appropriate ML algorithms and tools
• Develop machine learning applications according to requirements
• Select appropriate datasets and data representation methods
• Run machine learning tests and experiments
• Perform statistical analysis and fine-tuning using test results
• Train and retrain systems when necessary
• Extend existing ML libraries and frameworks, python, pytorch, tensorflow framework and edge computing
• Good understanding of ML Pipeline
• Keep abreast of developments in the field
• Skill