Senior AI/ML Engineer – R01571293

Brillio; Bengaluru; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Brillio is seeking an experienced data scientist to design and deploy advanced ML models for business challenges. You will work with Python, SQL, and leading ML frameworks, and collaborate with cross-functional teams.

Responsibilities include EDA, statistical analysis, model deployment on GCP, and maintaining data quality with validation tools. Knowledge of KubeFlow, BentoML, and forecasting methods is a plus for driving impactful insights.

Qualifications

• 2–4 years in advanced data science and ML roles.
• Hands-on with Python, SQL and ML frameworks.
• Experience deploying models on cloud platforms (GCP).

Responsibilities

• Design and develop ML models with classic and deep learning methods.
• Perform extensive EDA and statistical analyses to extract insights.
• Deploy and monitor AI models on Google Cloud Platform.
• Collaborate with cross-functional teams to integrate AI into workflows.
• Utilize KubeFlow and BentoML for orchestration and deployment.
• Conduct forecasting using exponential smoothing, ARIMA, and ARIMAX.
• Apply probabilistic graph models to improve predictive accuracy.
• Maintain data quality using Great Expectations and Evidently AI.

Skills

Python

SQL

Statistical analysis

Forecasting

Machine learning

Hypothesis testing

T-Test

Z-Test

Education

Bachelor's degree

Data science certification

Cloud certification

Tools

TensorFlow

PyTorch

Sci-Kit Learn

CNTK

Keras

MXNet

KubeFlow

BentoML

Great Expectations

Evidently AI

NumPy

Pandas

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