Senior Engineer, Applications & Platforms – R01570286

Brillio; Bengaluru; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

Brillio in Bengaluru seeks a senior data architect/AI architect with 7–10 years of experience to design data pipelines and AI solutions. You will build statistical and AI models and lead their production deployment with modern tools and frameworks.

Your role emphasizes data quality, collaboration with data scientists and engineers, and adopting emerging technologies to drive scalable analytics and AI initiatives.

Qualifications

• At least a Bachelor's degree in CS/DS/Statistics or math.
• 7–10 years of experience in data architecture, data science, analytics, and AI.
• Certifications in Data/AI fields are a plus.

Responsibilities

• Design and architect robust data pipelines and frameworks for analytics, ML, and AI workloads
• Develop and implement statistical and AI models, including regression, classification, forecasting, and deep learning
• Lead integration of probabilistic graph models, statistical tests, and AI solutions into production systems
• Collaborate with data scientists and engineers to optimize data workflows and AI model deployment using KubeFlow and BentoML
• Ensure data quality and integrity by implementing validation frameworks like Great Expectations and Evidently AI
• Manage and optimize large-scale data processing and AI environments using Python, PySpark, R, and SAS/SPSS
• Evaluate and select ML/AI frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet) for scalable deployment
• Provide technical leadership in the adoption of emerging technologies and best practices in data architecture, analytics, and AI

Skills

Python

PySpark

Statistics

Hypothesis testing

Regression

Probabilistic graphs

Data validation

KubeFlow

BentoML

Deep learning

Classification

Education

Bachelor’s degree in CS/DS/Statistics/Mathematics

Tools

SAS

SPSS

R

R Studio

TensorFlow

PyTorch

Sci-Kit Learn

CNTK

Keras

MXNet

Job description

Experience Range: With at least 7 to 10 years of experience in data architecture, data science, advanced statistical modeling, and AI architecture

Key Responsibilities:

• Design and architect robust data pipelines and frameworks to support advanced analytics, machine learning, and AI workloads
• Develop and implement statistical and AI models, including regression (linear and logistic), classification algorithms, forecasting techniques (ARIMA, exponential smoothing), and deep learning architectures
• Lead the integration of probabilistic graph models, advanced statistical tests (hypothesis testing, T-Test, Z-Test), and AI-driven solutions into production systems
• Collaborate with data scientists and engineering teams to optimize data workflows and AI model deployment using tools such as KubeFlow and BentoML
• Ensure data quality and integrity by implementing validation frameworks like Great Expectations and Evidently AI
• Manage and optimize large-scale data processing and AI environments using Python, PySpark, R, and SAS/SPSS
• Evaluate and select appropriate machine learning and AI frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet) for scalable model deployment
• Provide technical leadership in the adoption of emerging technologies and best practices in data architecture, advanced analytics, and AI solutions

Required Skills:

• Advanced proficiency in Python and PySpark
• Expertise in statistical analysis and computing
• Hands-on experience with SAS and SPSS
• Strong knowledge of hypothesis testing, T-Test, and Z-Test
• Experience with regression techniques (linear and logistic)
• Proficiency in probabilistic graph models
• Familiarity with Great Expectations and Evidently AI for data validation
• Forecasting expertise using ARIMA, ARIMAX, and exponential smoothing
• Working knowledge of KubeFlow and BentoML
• Experience with classification algorithms (Decision Trees, SVM)
• Experience architecting AI solutions and deploying deep learning models

Preferred Skills:

• Advanced experience with ML and AI frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet
• Expertise in distance metrics (Hamming, Euclidean, Manhattan)
• Proficiency in R and R Studio
• Experience with scalable AI model deployment in cloud environments
• Knowledge of automated model monitoring, drift detection, and AI lifecycle management

Desired Qualifications:

• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline
• Certification in Data Architecture, Data Science, or AI (e.g., Certified Data Professional, Microsoft Certified: Azure Data Scientist Associate, AI Architect certification)
• Certification in Machine Learning frameworks or platforms (e.g., TensorFlow Developer Certificate, AWS Certified Machine Learning – Specialty)