103 Quess Jobs

Role Details :

1. Delivering high quality AI models that meet the specified requirements and objectives of the project.

2. Conducting thorough experimentation, evaluation, and validation to ensure that the models perform accurately and reliably in real world scenarios.

3. Implementing scalable and efficient infrastructure for training and deploying AI models.

4. Enable seamless integration and deployment of AI solutions while optimizing resource utilization and cost effectiveness.

5. Contribute to the continuous improvement of AI systems through ongoing research, experimentation, and innovation.

6. Manage product deployment and be available for 24x7 support for production issues.

7. Prepare LLD, HLD and Deployment documents and support A in carrying out proper validation.

8. Load testing of Solution using various tools and automating the process so that QA can efficiently carry out similar activity.

9. Liaison with different teams for integration of different products and chart out effective strategy for seamless integration.

Skills & Attributes :

1. Programming Language - Java, Python (including Pandas, Numpy)

2. Good understanding of Mathematics, Statistics, Probability, Linear Algebra and Calculus.

3. Strong hands-on experience on at least one of the Machine Learning Framework such as Scikit-Learn, TensorFlow, PyTorch, keras etc.

4. Ability to visualize and understand the data using Pandas, NumPy, SQL etc.

5. Expert in data cleaning, data visualization, data preprocessing, data normalization

6. Fundamentally strong in ML algorithms from key ML domains - Regression, Classification, Clustering, Reinforcement Learning etc.

7. Hands on experience on Deep learning such as CNN, RNN, LSTM, Transformer Model creation, model training, model accuracy optimization and hyper parameter turning.

8. Good to have deep understanding of Gen AI - Training, Fine Tuning, Inference, Prompt Engineering, RAG, vectorization, Similarity search etc.

9. Exposure on NLP and Computer Vision is a definitive plus.

10. Familiar with AI Development Tools such as Docker, Kubernetes, Notebook, AWS, Azure, GCP, Jupyter etc.

11. Familiar with Software Engineering practices - GIT, Version control, testing, debugging, documentation etc.