Responsibilities :

Model Development:

1.Design, develop, and implement state-of-the-art machine learning models using Tensor Flow.

 2.Collaborate with cross-functional teams to understand project requirements and translate them into effective machine learning solutions.

Data Processing and Feature Engineering:

1.Preprocess and clean large datasets for training machine learning models.

 2.Implement feature engineering techniques to enhance model performance.

Training and Optimization:

1.Train and fine-tune machine learning models to achieve optimal performance.

 2.Implement optimization techniques to improve the efficiency and speed of model training.

Validation and Testing:

1.Conduct thorough validation and testing of machine learning models to ensure accuracy and reliability

2.Troubleshoot and debug issues in the models to enhance overall performance.

Documentation:

1.Document the development process, model architectures, and key decisions made during the project.

 2.Provide clear and concise documentation for models and code developed.

Collaboration:

1.Collaborate with software developers, data scientists, and other team members to integrate machine learning models into the project seamlessly.

2.Participate in code reviews and knowledge-sharing sessions to foster a collaborative and innovative environment.

Qualifications:

• Proven experience in developing machine learning models using Tensor Flow.
• Strong programming skills in Python and proficiency in relevant libraries (NumPy, Pandas, etc.).
• Solid understanding of deep learning concepts and architectures.
• Experience with GPU acceleration for deep learning tasks is a plus.
• Excellent problem-solving and critical-thinking skills.
• Strong communication skills and ability to work in a collaborative team environment.