Machine Learning Engineer

- Strong understanding of various machine learning algorithms, such as linear regression, logistic regression, decision trees, SVM, neural networks, ensemble methods, and reinforcement learning.
- Demonstrated experience in working with large datasets and using big data technologies, such as Hadoop, Spark, and distributed computing.
- Proficient in programming languages, such as Python.
- Experience with machine learning frameworks and libraries, such as TensorFlow, Keras, PyTorch, or Scikit-learn.
- Familiarity with data visualization tools, such as Tableau, Matplotlib, or D3.js.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration skills, with the ability to explain complex concepts to both technical and non-technical stakeholders.
Preferred Qualifications:
- Experience in working with cloud platforms, such as AWS, Google Cloud, or Azure.
- Knowledge of natural language processing, computer vision, or deep learning techniques.
- Experience developing end-to-end machine learning pipelines, from data gathering and pre-processing to model deployment and monitoring