AI/ML Engineer

Zorba AI; Kolkata District; In loco; INR 1.500.000 - 3.500.000; Tempo pieno

Descrizione del lavoro

Zorba AI in India seeks a hands-on AI/ML Engineer with 4+ years of experience who can design, train, evaluate, optimize, and deploy models from scratch.

You will apply strong ML, DL, statistics and Python skills to build end-to-end solutions, from data preprocessing to monitoring in production.

The role involves developing ML pipelines, performing hyperparameter tuning, and delivering robust models for real-world projects.

Competenze

• Hands-on AI/ML Engineer with strong foundations in ML, DL, statistics, and Python.
• Experience taking ML models from experimentation to production.
• Experience end-to-end ML solutions: data prep, feature engineering, training, deployment, monitoring.

Mansioni

• Design, develop, and implement machine learning models from scratch based on business requirements.
• Perform data collection, cleaning, preprocessing, exploratory data analysis, and feature engineering.
• Select appropriate algorithms and develop supervised and unsupervised models.
• Implement regression, classification, clustering, and ensemble learning techniques.
• Develop Deep Learning, NLP, and Generative AI solutions based on project requirements.
• Build end-to-end ML pipelines covering data preparation, model training, validation, deployment, and monitoring.
• Perform hyperparameter tuning, model optimization, error analysis, and performance benchmarking.

Descrizione del lavoro

We are looking for a hands-on AI/ML Engineer with 4+ years of experience who can independently design, develop, train, evaluate, optimize, and deploy machine learning models from scratch. The ideal candidate should have strong foundations in Machine Learning, Deep Learning, Statistics, and Python programming, along with proven experience in taking ML models from experimentation to production.

The candidate must have practical experience building end-to-end machine learning solutions, including data preprocessing, feature engineering, model training, performance optimization, deployment, and monitoring.

Key Responsibilities

• Design, develop, and implement machine learning models from scratch based on business requirements.
• Perform data collection, cleaning, preprocessing, exploratory data analysis, and feature engineering.
• Select appropriate algorithms and develop supervised and unsupervised machine learning models.
• Implement regression, classification, clustering, and ensemble learning techniques.
• Develop Deep Learning, NLP, and Generative AI solutions based on project requirements.
• Build end-to-end ML pipelines covering data preparation, model training, validation, deployment, and monitoring.
• Perform hyperparameter tuning, model optimization, error analysis, and performance benchmarking.