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Machine Learning Engineer
7 days ago
We are seeking a talented and experienced Machine Learning Engineer to join our growing team remotely.
You will play a key role in designing, developing, and deploying machine learning models to solve real-world business problems.
Leveraging your expertise in various machine learning algorithms and tools, you will contribute to the development and implementation of innovative solutions that drive business value.
Mandatory Key Skills:
Machine Learning Expertise:
- Minimum of 5 years of experience in Machine Learning model development and deployment.
- Strong understanding of supervised and unsupervised learning algorithms (e.g, classification, regression, clustering).
- Experience with deep learning frameworks like PyTorch or TensorFlow for computer vision or other applications (a plus).
- Familiarity with model evaluation metrics and techniques for performance optimization.
Programming Skills:
- Proficiency in Python for data manipulation, model development, and scripting.
- Working knowledge of object-oriented programming (OOP) concepts.
- Experience with scientific computing libraries like NumPy and pandas.
Data Management and Analysis:
- Ability to work with and clean large datasets for machine learning projects.
- Familiarity with SQL for querying relational databases (a plus).
Cloud Platforms:
- Experience with deploying and managing machine learning models on cloud platforms (AWS, Azure, GCP) is a plus.
Communication and Collaboration:
- Excellent communication skills to collaborate effectively with data scientists, engineers, and other stakeholders.
- Ability to clearly document and explain technical concepts to both technical and non-technical Work closely with data scientists and product managers to understand business problems and translate them into machine learning solutions.
- Design, develop, and train machine learning models using appropriate algorithms and techniques.
- Perform data preprocessing, feature engineering, and model selection for optimal performance.
- Evaluate and interpret model results, identify areas for improvement, and iterate on models.
- Deploy and monitor machine learning models in production environments (a plus).
- Stay up-to-date with the latest advancements in machine learning and related technologies
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