Generative AI Architect - Python

Key Responsibilities :

- Solution Design : Collaborate with cross-functional teams to define AI use cases, gather requirements, and architect end-to-end AI solutions that align with business goals.

- Algorithm Development : Develop and implement machine learning and deep learning algorithms, models, and frameworks to solve intricate problems and enhance system capabilities.

- Data Processing : Oversee data collection, preprocessing, and feature engineering to ensure high-quality input for AI models.

- Model Training and Evaluation : Train and fine-tune machine learning models using large datasets and rigorously evaluate model performance using appropriate metrics.

- Infrastructure and Tools : Design the AI infrastructure, choose suitable frameworks, libraries, and tools, and ensure scalability, reliability, and efficiency of AI systems.

- Prototyping and POCs : Build rapid prototypes and proof of concepts (POCs) to demonstrate the feasibility and potential of AI solutions.

- Technical Leadership : Provide technical guidance, mentorship, and support to AI development teams, fostering a culture of innovation and collaboration.

- Research and Innovation : Stay abreast of AI trends, emerging technologies, and best practices, and contribute to the company's AI strategy by proposing innovative solutions.

- Deployment and Integration : Lead the deployment of AI solutions into production environments, integrating them with existing systems and workflows.

- Performance Optimization : Continuously optimize AI solutions for speed, efficiency, and accuracy, and address any bottlenecks or issues.

- Documentation : Create comprehensive technical documentation, including design specifications, architecture diagrams, and code comments.

Qualifications and Requirements :

- Proven experience as an AI Engineer, Machine Learning Engineer, or AI Architect, with a track record of successful AI solution design and implementation.

- Streamlit - Python

- Generative AI

- HuggingFace , OpenAi and any Custom Model development experience

- Strong programming skills in languages such as Python, Java, or C++, and proficiency in AI libraries and frameworks (TensorFlow, PyTorch, scikit-learn, etc.).

- In-depth knowledge of machine learning techniques, algorithms, and model evaluation.

- Familiarity with big data technologies, cloud platforms, and distributed computing.

- Excellent problem-solving abilities and analytical thinking.

- Effective communication skills to collaborate with cross-functional teams and present technical concepts to both technical and non-technical stakeholders.

- Demonstrated ability to lead technical projects, drive innovation, and mentor junior team members.