Senior AI/ML Engineer - R01571293

Brillio 2; Bengaluru; Hybrid; INR 2,500,000 - 3,500,000; Full time

Job summary

Brillio 2 in Bengaluru seeks a Senior AI/ML Engineer to design and deploy advanced models, using classic algorithms and deep learning on large datasets.

You will collaborate with cross‑functional teams, perform EDA and forecasting, and implement production‑grade solutions on GCP, with emphasis on model quality and reliable deployment. Strong Python/SQL skills and experience with ML frameworks are required to translate business problems into scalable analytics.

Qualifications

• Must have 2-4 years hands-on experience in advanced data science, ML, and AI engineering roles.
• Proficient in Python and SQL with experience in ML algorithms and DL frameworks.
• Experience deploying AI/ML models on Google Cloud Platform (GCP).
• Familiar with model orchestration and deployment tools like KubeFlow and BentoML.
• Experience with forecasting methods such as exponential smoothing, ARIMA, and ARIMAX.
• Knowledge of data quality frameworks like Great Expectations and Evidently AI.

Responsibilities

• Design and develop advanced ML models using classic algorithms and deep learning to address complex business challenges.
• Conduct exploratory data analysis (EDA) and statistical analysis, including hypothesis testing, regression, and classification.
• Implement, optimize, and deploy AI/ML models on GCP with scalable production readiness.
• Collaborate with cross-functional teams to define data requirements and validate model outputs.
• Utilize KubeFlow and BentoML for model orchestration, deployment, and monitoring.
• Perform rigorous forecasting to support data-driven business planning.
• Apply probabilistic graph models and advanced statistical methods for predictive accuracy.
• Maintain data quality and model performance using Great Expectations and Evidently AI.

Skills

Python

SQL

Statistical analysis

Hypothesis testing

Regression

Classification

Time series forecasting

Probabilistic graph models

Model deployment

KubeFlow

BentoML

Great Expectations

Evidently AI

Education

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

Certification in machine learning or data science (TensorFlow Developer Certificate or Google Professional ML Engineer)

Certification in cloud technologies (Google Cloud Certified - Professional Data Engineer)

Tools

TensorFlow

PyTorch

Sci-Kit Learn

CNTK

Keras

MXNet

KubeFlow

BentoML

Job description

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

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 analysing 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 recognised platforms such as TensorFlow Developer Certificate or Google Professional Machine Learning Engineer
• Certification in cloud technologies, for example Google Cloud Certified - Professional Data Engineer