We are seeking an experienced and highly skilled Applied
AI/ML Lead to lead the design, development, and deployment of AI/ML
solutions for real -world business use cases. This role focuses on translating
AI research and models into production -ready, scalable solutions that
deliver measurable business impact.

As an AI/ML Lead, you will collaborate closely with
cross -functional teams including Data Analytics, Engineering, and Product,
influence AI -driven business strategies, and mentor a growing AI/ML team while
staying current with emerging AI technologies.

Roles & Responsibilities

- Lead
the development, deployment, and optimization of AI/ML models for
customer -facing applications.

- Drive
AI initiatives focused on personalization, recommendations, and
predictive analytics.

- Collaborate
with Data Analytics, Data Engineering, and Development teams to integrate
AI models into production systems.

- Design
and implement AI solutions using clustering, segmentation, and scoring
techniques.

- Ensure data readiness, quality, and pipeline reliability for AI/ML
workloads.

- Oversee
the development of AI/ML -based features and capabilities aligned with
business goals.

- Implement AIOps practices to monitor model performance and reduce MTTR (Mean
Time to Resolution).

- Mentor




and provide technical leadership to junior AI/ML engineers and data
scientists.

- Continuously
evaluate and adopt new AI/ML technologies and best practices.


Must -Have Skills

- 8+
years of experience in AI/ML, with at least 3 years in a
leadership or technical lead role.

- Strong
experience in applying AI/ML to business problems, especially
customer experience and personalization.

- Hands -on
expertise with TensorFlow, PyTorch, and scikit -learn.

- Strong
proficiency in Python for AI/ML development and deployment.

- Experience
integrating AI/ML models with cloud platforms (AWS preferred).

- Hands -on
exposure to AWS AI/ML services such as SageMaker or equivalent.

- Deep
understanding of customer segmentation, scoring, and recommendation
systems.

- Experience
working with real -time data systems and pipelines (e.g., Kafka).

- Robust
understanding of end -to -end ML lifecycle management from
experimentation to production.


Good to Have

- Experience
with MinIO and S3 for large -scale data storage.

- Exposure
to workflow orchestration tools like Apache Airflow.

- Knowledge
or hands -on experience with LLMs (Large Language Models) and RAG
(Retrieval -Augmented Generation).

- Experience
in automating AI/ML pipelines and deployments.


Qualifications

- Bachelor’s
degree in Computer Science, Engineering, or a related technical
discipline.