ML Engineer for Structured Data
Budget: ₹600 – ₹1,500 INR
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I'm in need of a skilled ML Engineer to tackle various aspects related to structured data, including data preprocessing, model training, and model evaluation.
Key Responsibilities:
- Data Preprocessing: The hired individual should be adept at handling data cleansing, transformation and reduction. This includes tasks like normalization and dealing with missing values.
- Model Training: The ML Engineer will be responsible for training predictive models using the preprocessed data. The models should perform well in terms of accuracy and speed.
- Model Evaluation: After training, the models need to be rigorously evaluated. The ML Engineer should be capable of assessing and fine-tuning models to ensure optimal performance.
Key Requirements:
- Proficiency in Python and Java: The ideal candidate should have a strong background in Python and Java, as these languages will be heavily used in the project.
- Experience with Structured Data: Prior experience working with structured data and spreadsheets is essential. Familiarity with tools and techniques for handling such data is a big plus.
- Strong Machine Learning Background: A deep understanding of machine learning concepts, algorithms, and frameworks is crucial. The ML Engineer should be able to select and implement appropriate models for the given task.
If you believe you have the right skill set and experience for this project, please reach out with your relevant qualifications.
I'm in need of a skilled ML Engineer to tackle various aspects related to structured data, including data preprocessing, model training, and model evaluation.
Key Responsibilities:
- Data Preprocessing: The hired individual should be adept at handling data cleansing, transformation and reduction. This includes tasks like normalization and dealing with missing values.
- Model Training: The ML Engineer will be responsible for training predictive models using the preprocessed data. The models should perform well in terms of accuracy and speed.
- Model Evaluation: After training, the models need to be rigorously evaluated. The ML Engineer should be capable of assessing and fine-tuning models to ensure optimal performance.
Key Requirements:
- Proficiency in Python and Java: The ideal candidate should have a strong background in Python and Java, as these languages will be heavily used in the project.
- Experience with Structured Data: Prior experience working with structured data and spreadsheets is essential. Familiarity with tools and techniques for handling such data is a big plus.
- Strong Machine Learning Background: A deep understanding of machine learning concepts, algorithms, and frameworks is crucial. The ML Engineer should be able to select and implement appropriate models for the given task.
If you believe you have the right skill set and experience for this project, please reach out with your relevant qualifications.
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