Machine Learning Engineer

3 weeks ago


Ahmedabad, India Flipped.ai Full time

Key Responsibilities :

The Machine Learning Engineer will be responsible for designing, building, and deploying machine learning models and systems. This role requires strong technical skills, a good understanding of machine learning principles, and the ability to work collaboratively with cross-functional teams.

Job Summary :

- Develop CV Models: Passion for meaningful selling, ensuring clients see real value and ROI from their investments in our streaming solutions.


- Data Collaboration: Collect, preprocess, and annotate sports images and videos.


- Model Customization: Choose and customise CNN architectures (e.g., ResNet, VGG, MobileNet).


- Model Training: Train, optimise, test, and validate models using TensorFlow or PyTorch.


- Model Deployment: Deploy and maintain models for real-time video analysis and classification.


- Performance Monitoring:Monitor and optimise model performance.


- System Integration: Integrate CV solutions into applications and systems.


- Algorithm Improvement: Regularly refine and improve algorithms.


- Scalability: Ensure CV solutions are scalable and robust.


What You Need to Bring to the 'Pitch' :

- Experience: Experience in computer vision-related algorithms.


- Educational Background: Experience in computer vision-related Skills :


- Proficiency in TensorFlow, PyTorch.


- Experience with data annotation tools.


- Understanding CNN architectures.


- Familiarity with image and video processing techniques.


- Programming Skills: Proficiency in Python, R, or Java.


- ML Frameworks: Experience with TensorFlow, PyTorch, or scikit-learn.


- Technical Proficiency: Strong understanding of data structures, algorithms, and software design.


- Cloud Platforms: Experience with AWS, GCP, or Azure is a plus.


- Analytical Skills: Excellent problem-solving skills and attention to detail.


- Collaboration: Strong communication and collaboration abilities.


Preferred Qualifications :


- Experience in sports analytics.


- Knowledge of real-time video processing.

(ref:hirist.tech)
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