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Senior AI/ML Engineer - R01570503 en Brillio-2

Brillio-2 · Bangalore, India · Hybrid

Python

SQL

Google Cloud Platform

Cloud

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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
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