AI Engineer

Skyleaf Consultants; Gurugram District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Skyleaf Consultants in India is seeking an experienced Machine Learning Engineer to design, develop, and deploy ML and AI models that power analytics and BI initiatives. The role emphasizes building scalable pipelines and collaborating with data engineers.

You'll translate business problems into ML solutions, implement monitoring and governance, and stay current with TensorFlow, PyTorch, scikit-learn, and cloud ML platforms.

Qualifications

• Advanced proficiency in Python, R, or similar languages; familiarity with ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Strong understanding of machine learning algorithms, statistical modeling, and data science fundamentals.
• Experience with cloud ML platforms (Azure ML, AWS SageMaker, Google Vertex AI) and model deployment pipelines.
• Knowledge of data warehouse/lake architecture and SQL for efficient data access.
• Familiarity with ML Ops practices, model versioning, and CI/CD for machine learning.
• Strong problem-solving skills and ability to translate business requirements into technical solutions.

Responsibilities

• Design, develop, and deploy machine learning and AI models to support advanced analytics and business intelligence initiatives.
• Build and optimize end-to-end machine learning pipelines, including data preprocessing, feature engineering, model training, and model evaluation.
• Collaborate with data engineers to ensure data quality, scalability, and efficient data access for AI/ML workloads.
• Partner with business analysts and stakeholders to translate business problems into ML/AI solutions and measurable outcomes.
• Implement AI model monitoring, validation, and governance practices to ensure production performance and compliance.
• Stay current with emerging AI/ML technologies, frameworks (TensorFlow, PyTorch, scikit-learn), and best practices.
• Support experimentation, POCs, and feasibility studies for new AI/ML capabilities.
• Document models, algorithms, and technical implementations for knowledge transfer and audit trails.

Skills

Python

R

ML frameworks

Data analysis

CI/CD for ML

Tools

TensorFlow

PyTorch

scikit-learn

Azure ML

AWS SageMaker

Google Vertex AI

Job description

Role & responsibilities

• Design, develop, and deploy machine learning and AI models to support advanced

analytics and business intelligence initiatives.

• Build and optimize end-to-end machine learning pipelines, including data preprocessing,

feature engineering, model training, and model evaluation.

• Collaborate with data engineers to ensure data quality, scalability, and efficient data

access for AI/ML workloads.

• Partner with business analysts and stakeholders to translate business problems into

ML/AI solutions and measurable outcomes.

• Implement AI model monitoring, validation, and governance practices to ensure

production performance and compliance.

• Stay current with emerging AI/ML technologies, frameworks (TensorFlow, PyTorch,

scikit-learn), and best practices.

• Support experimentation, POCs, and feasibility studies for new AI/ML capabilities.
• Document models, algorithms, and technical implementations for knowledge transfer

and audit trails.

Preferred candidate profile

• Advanced proficiency in Python, R, or similar languages; familiarity with ML frameworks

(TensorFlow, PyTorch, scikit-learn).

• Strong understanding of machine learning algorithms, statistical modeling, and data

science fundamentals.

• Experience with cloud ML platforms (Azure ML, AWS SageMaker, Google Vertex AI) and

model deployment pipelines.

• Knowledge of data warehouse/lake architecture and SQL for efficient data access.
• Familiarity with ML Ops practices, model versioning, and CI/CD for machine learning.
• Strong problem-solving skills and experience translating business requirements into

technical solutions.