
Machine Learning Engineer
2 weeks ago
Are you passionate about AI and fintech? Do you want to join a company that is building cutting-edge technology to transform the financial industry and empower traders? If yes, then we have an exciting opportunity for you
We are looking for talented and motivated individuals who share our vision and want to make a difference in the world.
We are looking for a machine learning engineer to join our team and help us develop and deploy innovative solutions for various business problems. You will be responsible for designing, building, testing, and maintaining machine learning models and pipelines that can handle large-scale data and deliver high-quality results.
**## Responsibilities**
- Understand the business requirements and objectives of the projects and translate them into machine learning problems.
- Research, evaluate, and implement state-of-the-art machine learning algorithms and frameworks for various tasks such as classification, regression, clustering, anomaly detection, natural language processing, computer vision, etc.
- Develop and optimize data processing and feature engineering pipelines to prepare data for machine learning models.
- Train, validate, and test machine learning models using appropriate metrics and methods.
- Deploy and monitor machine learning models in production environments using cloud platforms and tools.
- Communicate and collaborate with other engineers, data scientists, product managers, and stakeholders to deliver end-to-end solutions.
**## Requirements**
- Bachelor's degree or higher in computer science, engineering, mathematics, statistics, or related fields.
- Proven experience in developing and deploying machine learning solutions using Python, TensorFlow, PyTorch, Scikit-learn, or other frameworks and libraries.
- Solid understanding of machine learning concepts, techniques, and best practices such as data preprocessing, feature engineering, model selection, hyperparameter tuning, validation, testing, etc.
- Experience with SQL and NoSQL databases and big data technologies such as Spark, Hadoop, Kafka, etc. is a plus.
- Excellent communication and presentation skills and ability to work in a team.
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