Artificial Intelligence Engineer

Solarix Technologies; Gurugram District; On-site; INR 800,000 - 1,600,000; Full time

Job summary

Solarix Technologies in Gurugram, India, seeks an ML Engineer to design, develop, and deploy machine learning and AI models for advanced analytics initiatives. You will contribute to end-to-end data pipelines and collaborate with cross-functional teams to translate business problems into measurable ML outcomes.

Responsibilities include model development, monitoring, and governance, with ongoing learning of TensorFlow, PyTorch, scikit-learn, and modern MLOps practices; participation in

Qualifications

• ,
• Hands-on experience building ML models and pipelines.
• Experience with cloud ML platforms and data access.
• Good problem-solving and collaboration with stakeholders.

Responsibilities

• Design, develop, and deploy ML/AI models for analytics.
• Build end-to-end ML pipelines: preprocessing, training, evaluation.
• Collaborate with data engineers to ensure data quality and access.
• Translate business problems into ML solutions with measurable outcomes.
• Implement monitoring, validation, and governance for production models.
• Stay updated with TensorFlow, PyTorch, scikit-learn and best practices.
• Support experiments, POCs, and feasibility studies.
• Document models and algorithms for knowledge transfer.

Skills

Python

R

SQL

ML Fundamentals

Cloud ML

ML Ops

Problem Solving

Tools

TensorFlow

PyTorch

scikit-learn

Data Warehousing

Job description

Responsibilities

• Design, develop, and deploy machine learning and Al 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 Al/ML workloads.
• Partner with business analysts and stakeholders to translate business problems into ML/Al solutions and measurable outcomes.
• Implement Al model monitoring, validation, and governance practices to ensure production performance and compliance.
• Stay current with emerging Al/ML technologies, frameworks (TensorFlow, PyTorch, scikit-learn), and best practices.
• Support experimentation, POCs, and feasibility studies for new Al/ML capabilities.
• Document models, algorithms, and technical implementations for knowledge transfer and audit trails.

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 Al) 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.