Senior AI/ML Engineer - R01571293

Brillio; Bengaluru; On-site; INR 1,200,000 - 2,300,000; Full time

Job summary

Brillio in Bengaluru is seeking a Senior AI/ML Engineer with 2–4 years of hands-on data science, ML and AI engineering experience to design and deploy advanced models.

You will work with Python and SQL, use TensorFlow, PyTorch, Scikit-learn, and other frameworks; deploy on Google Cloud, orchestrate with KubeFlow and BentoML, perform EDA, forecasting, and ensure data quality with Great Expectations.

Qualifications

• Hands-on data science, ML and AI engineering experience.
• Proficiency in Python and SQL for data manipulation and modeling.
• Experience with ML frameworks and model deployment.

Responsibilities

• Design and develop advanced ML models using classic and deep learning techniques.
• Conduct exploratory data analysis and statistical testing to extract insights.
• Deploy AI/ML models on Google Cloud Platform with scalable production readiness.
• Collaborate with cross-functional teams to integrate AI into workflows.
• Use KubeFlow and BentoML for model orchestration and monitoring.
• Perform forecasting using exponential smoothing, ARIMA, and related methods.
• Apply probabilistic graph models and maintain data quality with GE and Evidently.

Skills

Python

SQL

ML & AI

Statistical analysis

Forecasting

Hypothesis testing

Model deployment

EDA

Data quality

Interpretability

Education

Bachelor's degree in CS/DS

TensorFlow Developer Certificate

Google Professional ML Engineer

Tools

TensorFlow

PyTorch

Scikit-learn

CNTK

Keras

MXNet

GCP

KubeFlow

BentoML

Great Expectations

Evidently AI

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