Senior Machine Learning Engineer

BlackStone eIT, a leading computer software company, is seeking a highly skilled and experienced Senior Machine Learning Engineer to join our dynamic team. As a Senior Machine Learning Engineer at BlackStone eIT, you will be responsible for designing, developing, and deploying state-of-the-art machine learning models and algorithms. You will work closely with cross-functional teams to analyze complex data, identify opportunities for applying machine learning techniques, and lead the development and implementation of solutions to solve challenging business problems.

In this role, you will have the opportunity to work on cutting-edge projects, collaborate with industry experts, and make significant contributions to the company's success. We are seeking individuals who are passionate about machine learning, possess strong analytical and problem-solving skills, and have a proven track record in delivering successful machine learning solutions.

• Experience: 3-5 years
• 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
• Outstanding analytical and problem-solving skills
• Familiarity with machine learning frameworks (like Tensorflow or PyTorch) and libraries (like scikit-learn)
• Excellent communication skills

• Ability to work in a team

• BSc in Computer Science, Mathematics or a similar field; a Master's degree is a plus

Responsibilities

• ·         Study and transform data science prototypes
• ·         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
• ·         Deploy the trained models and build REST APIs
• ·         Perform statistical analysis and fine-tuning using test results
• ·         Train and retrain systems when necessary
• ·         Extend existing ML libraries and frameworks
• ·         Study project Requirements
• ·         write technical details at BRDs
• ·         Keep abreast of developments in the field
  

• Paid Time Off
• Work From Home
• Performance Bonus
• Training & Development