Architect and Practice Head (AI and Gen AI)

Need an Architect in AI with implementing machine learning

- We are seeking a highly motivated and self-driven AI Experienced Leader to head our AI and Gen AI practice.

- The successful candidate will be responsible for designing and implementing AI and Gen AI-based solutions to address customer business problems.

Key Responsibilities:

AI Solution Consultant:

- Understand customer needs and propose AI and Gen AI solutions to address business problems.

AI Practice Head:

- Research industry advancements in AI and Gen AI to identify practical, differentiating solutions for business problems.

- Build and inspire a strong team of Data Scientists to deliver complex AI and Gen AI programs.

AI Solution Architect:

- Define architecture, design solutions, and implement AI and Gen AI-based solutions for customer programs.

- Conduct architecture reviews, design workshops, and code reviews in collaboration with AI Data Scientists and Cloud Engineers.

Implementation and Optimization:

- Apply statistics, modeling, and machine learning to improve system efficiency and algorithm relevance.

- Build scalable Machine Learning solutions and ensure their practical use in production environments.

Skills and Qualifications:

- Bachelor's or Master's degree in Computer Science, AIML, Data Sciences, or a related field.

- MBA will be a plus.

- 10+ years of experience in designing and implementing Machine Learning and Deep Learning models.

- Proficiency in R, Python (NumPy, Scikit-learn, Pandas), TensorFlow, PyTorch, MLlib, and LLM solutions.

- Strong problem-solving and analytical skills with the ability to translate business requirements into data science solutions.

- Experience in scripting SQL for extracting large data sets and designing ETL flows.

- Deep interest in data, metrics, analysis, trends, and a strong understanding of measurement, statistics, and program evaluation.

- Effective communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders