Job Description:

We are seeking an experienced Assistant Manager / Manager TFO (AI/ML) to lead the development and deployment of Artificial Intelligence and Machine Learning solutions that drive business transformation and operational excellence.

The ideal candidate will possess strong expertise in machine learning, predictive analytics, data engineering, and MLOps, with the ability to translate complex business challenges into scalable AI-driven solutions.

This role involves collaborating with business stakeholders, data engineers, software developers, and product teams to build intelligent applications, optimize AI models, and deliver measurable business impact.

Key Responsibilities:

- Design, develop, and deploy scalable Machine Learning and AI solutions for business use cases.

- Work closely with business stakeholders to identify opportunities for AI-driven automation and predictive analytics.

- Build and optimize supervised, unsupervised, and deep learning models for structured and unstructured data.

- Develop end-to-end ML pipelines covering data ingestion, feature engineering, model training, validation, deployment, and monitoring.

- Implement MLOps practices for continuous integration, model versioning, deployment, and performance monitoring.

- Collaborate with Data Engineering teams to build scalable data pipelines and ensure high-quality data availability.

- Perform exploratory data analysis (EDA), feature selection, and statistical modeling to improve model accuracy.

- Deploy AI models using cloud platforms and containerized environments.

- Monitor production models for drift, accuracy, latency, and overall performance.

- Optimize model performance through hyperparameter tuning and advanced ML techniques.

- Research emerging AI technologies and recommend innovative solutions to improve business outcomes.

- Prepare technical documentation, model reports, and presentations for leadership and business stakeholders.

- Mentor junior AI/ML engineers and promote best practices across the team.

Required Technical Skills :

- Strong hands-on experience in Artificial Intelligence and Machine Learning.

- Expertise in:

1. Python

2. Machine Learning Algorithms

3. Deep Learning

4. Natural Language Processing (NLP)

5. Computer Vision (preferred)

6. Predictive Analytics

7. Statistical Modeling

8. Feature Engineering

9. Model Evaluation & Optimization

- Experience with ML frameworks such as:

1. Scikit-learn

2. TensorFlow

3. PyTorch

4. XGBoost

5. Keras

- Strong programming skills in Python and SQL.

- Experience with data processing libraries such as Pandas, NumPy, and PySpark.

- Knowledge of MLOps tools such as MLflow, Kubeflow, Docker, Kubernetes, or Airflow.

- Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.

- Understanding of REST APIs and model deployment techniques.

Preferred Skills:

- Experience working on Generative AI and Large Language Models (LLMs).

- Exposure to Retrieval-Augmented Generation (RAG), LangChain, vector databases, and AI agents.

- Experience with Spark, Databricks, or distributed computing frameworks.

- Knowledge of CI/CD pipelines and DevOps practices.

- Familiarity with Git, Jira, and Agile methodologies.

- Exposure to BI and visualization tools such as Power BI or Tableau is an advantage.

Desired Candidate Profile:

- 4-9 years of experience in AI/ML, Data Science, or Advanced Analytics.

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, or a related field.

- Strong analytical, problem-solving, and critical thinking abilities.

- Excellent communication and stakeholder management skills.

- Ability to lead technical discussions and collaborate across cross-functional teams.

- Self-driven, innovative, and passionate about emerging AI technologies.

- Experience mentoring team members and delivering enterprise-scale AI projects.