Key Responsibilities :

- Design the architecture of scalable AI/ML platforms and solutions.

- Translate complex business problems into appropriate ML, Deep Learning, and Gen AI approaches.

- Develop and fine-tune predictive models, algorithms, and AI applications.

- Build efficient data and model pipelines to support large-scale AI workloads.

- Apply statistical techniques for experimentation, model validation, and performance evaluation.

- Develop reusable frameworks and components for AI/ML applications.

- Take models from prototype to production, including integration, deployment, and optimization.

- Improve model performance, scalability, latency, and reliability in production environments.

- Establish model observability and monitoring practices to track performance, data quality, drift, and system health.

- Work closely with Data Engineering, Product, Software Engineering, and Business teams to deliver production-ready AI solutions.

- Evaluate emerging AI/Gen AI technologies and identify opportunities for their practical adoption.

Required Skills :

- 5 - 8 years of experience in AI/ML, Machine Learning Engineering, or a related domain.

- Strong programming expertise in Python.

- Strong proficiency in SQL and data manipulation.

- Solid understanding of Machine Learning and Deep Learning algorithms.

- Hands-on experience with Generative AI technologies and use cases.

- Strong foundation in Statistics, model development, and evaluation techniques.

- Understanding of data engineering principles and large-scale data pipelines.

- Experience with AI/ML model deployment and production environments.

- Knowledge of model observability, monitoring, and performance optimization.

- Strong understanding of system architecture and scalable solution design.

Preferred Candidate Profile :

- Has built and deployed AI/ML solutions in production environments.

- Comfortable working across the complete AI lifecycle - data - experimentation - model - deployment - monitoring.

- Strong ownership of technical architecture and engineering decisions.

- Ability to work in a fast-paced environment and solve ambiguous, complex problems.