About the role
We are looking for a Dynamic individual
Responsibilities
- Develop and deploy machine learning models using MLOps best practices to ensure efficient and scalable deployment and monitoring of models in production.
- Collaborate with cross-functional teams to identify opportunities for leveraging machine learning techniques.
- Build and maintain scalable machine learning pipelines to process and analyze large datasets.
- Conduct data exploration, feature engineering, and model selection to improve predictive performance.
- Implement and optimize state-of-the-art algorithms and models for various machine learning tasks.
- Stay updated with the latest advancements in machine learning and propose innovative solutions to enhance client organizationsโ AI capabilities.
- Effective communication with foreign clients.
Requirements
- Strong proficiency in Python, including experience with machine learning libraries and frameworks such as TensorFlow or similar.
- Basic knowledge of Linear algebra, Calculus and Statistics.
- Strong problem-solving skills.
- Hands on experience with MLOps, and DevOps.
- Familiarity with ML cloud services (like Azure Machine Learning).
- Good communication skills in English.
- Ability to use cutting edge technologies like AI to efficiently deliver tasks.
- Nice To Have Requirements
- Fluency in R.
- Good Understanding of Data Engineering and ETL operations.
- Notable experience in Kaggle or other machine learning competitions.
Skills
Benefits
- Very competitive salary and long-term benefits with excellent career opportunity in a focused and stable organization.
- Great opportunity to work with global companies.
- A healthy work environment with opportunity to learn from a number of highly skilled engineers.
- Weekend: Saturday and Sunday.
How to apply
Apply through the employer using the Apply button. Include a current CV and, where relevant, links to your GitHub or portfolio. You will leave DataJobs BD; applications go to the employer's own site or email.