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 effective 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

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans.

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📌 Senior AI/ML Engineer503 (Bengaluru)
🏢 Brillio
📍 Bengaluru