Senior AI/ML Engineer – R01570503

Brillio; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Brillio is seeking a data science professional with 2–4 years of hands-on experience in advanced ML/AI roles in Bengaluru. You will design and deploy ML models, perform EDA and statistical analysis, and collaborate across teams to integrate AI into business processes.

Responsibilities include model development, deployment on GCP, forecasting, and maintaining data quality with frameworks like Great Expectations and Evidently AI.

Qualifications

• Hands-on experience with ML/AI projects in production.
• Strong statistical analysis and hypothesis testing skills.
• Experience with forecasting and time-series modeling.
• Proven ability to deploy models on cloud platforms.

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

Skills

Python

SQL

TensorFlow

PyTorch

Scikit-Learn

Keras

MXNet

Statistical Analysis

Hypothesis Testing

Forecasting

Model Deployment

GCP

EDA

Great Expectations

Evidently AI

Education

Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics

Tools

KubeFlow

BentoML

Job description

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

Required Skills:

• 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

Preferred Skills:

• Experience with GenAI and Agentic AI technologies
• Hands-on expertise with PySpark, SAS, or SPSS for large-scale statistical computing
• Proficiency in R and R Studio for statistical modeling and data visualization

Desired Qualifications:

• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline
• Certification in machine learning or data science from recognized platforms such as TensorFlow Developer Certificate or Google Professional Machine Learning Engineer
• Certification in cloud technologies, for example Google Cloud Certified - Professional Data Engineer