Senior AI/ML Engineer - R01570503

Brillio; Bengaluru; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Brillio in Bengaluru seeks an experienced Senior AI/ML Engineer to design, build and productionize advanced ML models. The role emphasizes end-to-end development from data exploration through deployment on GCP, with strong emphasis on forecasting and model interpretability.

You will collaborate with cross-functional teams, apply probabilistic methods, and ensure data quality using frameworks like Great Expectations and Evidently AI.

Qualifications

• 2-4 years of hands-on data science, ML and AI engineering experience.
• Strong Python and SQL for data manipulation and modeling.
• Experience with TF, PyTorch, Scikit-Learn, Keras, MXNet.
• Excellent statistical analysis: hypothesis testing, regression (linear/logistic).
• Experience with classification: decision trees and SVM.
• Forecasting: exponential smoothing, ARIMA, ARIMAX.
• Ability to implement probabilistic graph models.
• Familiarity with data quality tools: Great Expectations and Evidently AI.

Responsibilities

• Design and develop ML models using classic algorithms and deep learning.
• Conduct extensive EDA and statistical analysis to extract insights.
• Deploy AI/ML models on Google Cloud Platform for production use.
• Collaborate with cross-functional teams to define data requirements and integration points.
• Use KubeFlow and BentoML for model orchestration, deployment, and monitoring.
• Perform rigorous forecasting to support business planning.
• Apply probabilistic methods to improve predictive accuracy and interpretability.
• Maintain data quality and track model performance with key metrics.

Skills

Python

SQL

Statistical analysis

Hypothesis testing

Regression

Classification (DT,SVM)

Forecasting (ETS, ARIMA, ARIMAX)

Probabilistic graph models

Distance metrics

Great Expectations

Evidently AI

Education

Bachelor's degree (CS/DS/Stats/Math)

Tools

TensorFlow

PyTorch

Sci-Kit Learn

CNTK

Keras

MXNet

Job description

Senior AI/ML Engineer

Job requirements

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