Key Responsibilities

Design, develop, and deploy machine learning and AI models for real-world applications.
Build and maintain scalable APIs for model integration and consumption.
Perform data processing, feature engineering, and data analysis .
Manage the full lifecycle of ML models including:
- Training
- Evaluation
- Deployment
- Monitoring
Implement and manage MLOps pipelines for continuous integration and delivery of ML models.
Work on Model Context Protocol (MCP) integration for efficient AI system orchestration.
Collaborate with cross-functional teams to translate business requirements into AI-driven solutions .
Ensure performance, scalability, and reliability of deployed models.

Essential Technical Skills

Strong programming skills in Python .
Hands-on experience with machine learning frameworks:
- TensorFlow
- PyTorch
Experience in building and integrating RESTful APIs for models.
Proficiency in:
- Data preprocessing and feature engineering
- Model training and evaluation techniques
Experience with MLOps tools and practices (CI/CD, model monitoring, versioning).
Understanding of Model Context Protocol (MCP) .

Desirable Technical Skills

Exposure to cloud platforms (AWS, Azure, GCP).
Experience with containerization tools like Docker/Kubernetes .
Familiarity with big data tools and pipelines.
Knowledge of LLMs or Generative AI (optional but preferred).

Experience & Background

4 5 years of experience in AI/ML development .
Proven experience in building and deploying production-grade AI/ML solutions .
Strong exposure to applying AI in domains such as Telecom, eCommerce, or similar industries .
Experience working with cross-functional teams (engineering, product, business stakeholders).

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

AI Developer

Job Description

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