Experience : 4+ Years

Employment Type : Full-Time

Location : Gurugram

Role Overview :

We are looking for an experienced AI Engineer to design, develop, deploy, and maintain AI and Machine Learning solutions that enable data-driven decision-making and business innovation.

The role involves a combination of Machine Learning, Data Science, Software Engineering, Cloud Technologies, and MLOps to develop scalable AI models and production-ready ML pipelines.

The ideal candidate will work closely with data engineers, business stakeholders, business analysts, and technology teams to translate complex business challenges into impactful AI-driven solutions while ensuring model performance, reliability, governance, and continuous improvement.

Key Responsibilities :

- Design, develop, test, and deploy Machine Learning and AI models for advanced analytics and business intelligence initiatives.

- Build and optimize end-to-end ML pipelines, including data preprocessing, feature engineering, model training, validation, and evaluation.

- Collaborate with data engineering teams to ensure data quality, scalability, and efficient data access for AI/ML workloads.

- Work with business analysts and stakeholders to understand business requirements and translate them into effective AI/ML solutions.

- Implement model monitoring, validation, governance, and performance management practices for production ML models.

- Conduct experimentation, Proofs of Concept (POCs), and feasibility studies for emerging AI/ML capabilities.

- Deploy and maintain machine learning solutions across cloud environments.

- Follow MLOps best practices, including model versioning, CI/CD, deployment automation, and lifecycle management.

- Stay updated with emerging AI/ML technologies, frameworks, tools, and industry best practices.

- Document models, algorithms, technical implementations, and deployment processes to support knowledge transfer and audit requirements.

Required Skills & Qualifications :

- Strong hands-on proficiency in Python, R, or similar programming languages.

- Good understanding of Machine Learning algorithms, statistical modeling, and Data Science fundamentals.

- Hands-on experience with ML frameworks such as :

1. TensorFlow

2. PyTorch

3. Scikit-learn

- Experience with cloud-based ML platforms such as:

1. Azure Machine Learning

2. AWS SageMaker

3. Google Vertex AI

- Experience with ML model deployment and production pipelines.

- Strong knowledge of SQL and data warehouse/data lake architectures.

- Understanding of MLOps practices, model versioning, CI/CD, and ML lifecycle management.

- Strong analytical and problem-solving abilities.

- Ability to translate business requirements into scalable technical solutions.

- Good communication and stakeholder management skills.

Preferred Profile :

- Experience working on end-to-end AI/ML projects from experimentation through production deployment.

- Exposure to cloud-based AI/ML ecosystems and scalable ML architectures.

- Strong understanding of production model monitoring and governance.

- Ability to work collaboratively with data engineers, analysts, business stakeholders, and technology teams.

What We Offer :

- Opportunity to work on AI/ML and data-driven business solutions.

- Exposure to cloud technologies, MLOps, and production-grade machine learning environments.

- Growth opportunities in a rapidly evolving AI/ML domain.