Role & Responsibilities:

● Design and architect multi-layered ML solutions using Azure AI Foundry and ensuring they are robust, scalable, and production-ready.

● Defining and implementing robust integration strategies between legacy control software (e.g., VB6) and modern Azure ML platforms, ensuring seamless data flow, scalability, and strict data security governance.

● Architecting, developing, and deploying advanced machine learning and deep learning models specifically for curve prediction and automated quality scoring.

● Designing and implementing sophisticated optimization engines to automate precision movements with micron-level accuracy.

● Leading the transition from manual operator heuristics and rule-based systems to automated, data-driven logic and decision-making processes.

● Performing extensive data pre-processing on historical calibration data to train and validate models, and building robust production monitoring, alerting, and retraining scripts.

● Continuously enhancing, modifying, optimizing, and maintaining existing ML models to improve performance, accuracy, and efficiency.

● Working closely with external and internal stakeholders to define requirements for ML use cases, gather feedback, and drive solution enhancements.

● Generating actionable insights from large datasets and effectively communicating complex analysis results and model performance to clients and internal stakeholders.

● Provide technical leadership to MLEs and Platform engineers to ensure architectural alignment across workstreams.

Skills Expectation





● Expertise in Python and SQL with PySpark for large-scale data processing.

● Experience Expertise in Tree-based models (e.g., XGBoost, LightGBM).

● Strong foundation in Traditional ML algorithms (e.g., Logistic Regression, Cluster Analysis, Decision Trees, Statistical Modeling, Predictive Analysis, Regression, Classification).

● Experience with Encoder-Decoder architectures for sequence modeling.

● Proficiency in Deep Learning Architectures specifically for time series and curve data.

● Deep expertise in Agentic AI, Time Series forecasting, Descriptive Machine Learning, and Exploratory Data Analysis.

● Robust experience with Google Cloud Platform (GCP) Or Azure Cloud Services for ML workloads. ● Proven ability to design, develop, and deploy production-grade Machine Learning and Generative AI systems that deliver measurable ROI and contribute to long-term AI roadmaps.

● Experience with advanced optimization techniques for black-box functions, including Bayesian Optimization and sophisticated hyperparameter tuning methods.

● Experience with Databricks for ML workflows and data engineering.

● Must have experience in putting models into production.

● Experience in post-production deployment, including MLOps practices (monitoring, retraining, versioning), would be a significant plus.

● Experience working with scalable, highly-interactive, high-performance ML systems and projects. ● Great analytical skills with meticulous attention to detail.

● Strong stakeholder and team management skills.

📌 Associate Architect Machine Learning (Bengaluru)
🏢 Quantiphi
📍 Bengaluru