Senior AI/ML Engineer

Bangalore, Karnataka, India

AI & Data Engineering – AI & Data Engineering : Data Science /

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Senior AI/ML Engineer

Experience Range: With at least 2 to 4 years of hands-on experience in advanced data science, machine learning, and AI engineering roles Key Responsibilities:

* Design and develop advanced machine learning models using classic algorithms and deep learning techniques to address complex business challenges and deliver measurable improvements * Conduct comprehensive exploratory data analysis (EDA) and statistical analysis, including hypothesis testing, regression, and classification, to extract actionable insights from large datasets * Implement, optimize, and deploy AI/ML models on Google Cloud Platform (GCP), ensuring scalability, reliability, and efficient integration into production environments * Collaborate with cross-functional teams to define data requirements, validate model outputs, and integrate AI solutions seamlessly into existing workflows * Utilize KubeFlow and BentoML for efficient model orchestration, deployment, and monitoring, ensuring robust operational performance * Perform rigorous forecasting using methods such as exponential smoothing, ARIMA, and ARIMAX to support data-driven business planning * Apply probabilistic graph models and advanced statistical methods to enhance predictive accuracy and interpretability of AI solutions * Maintain high standards for data quality and model performance using frameworks like Great Expectations and Evidently AI, tracking key metrics and outcomes

* Proficiency in Python and SQL for data manipulation, analysis, and model development * Hands-on experience with classic machine learning algorithms and deep learning frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet * Expertise in statistical analysis including hypothesis testing, T-Test, Z-Test, and regression (linear, logistic) * Experience with classification techniques such as decision trees and support vector machines (SVM) * Knowledge of forecasting methods including exponential smoothing, ARIMA, and ARIMAX * Ability to implement and interpret probabilistic graph models * Familiarity with tools for model deployment and orchestration such as KubeFlow and BentoML * Competence in computing and analyzing distance metrics (Hamming, Euclidean, Manhattan) * Experience with data quality frameworks such as Great Expectations and Evidently AI