Quantiphi
Website:
quantiphi.com
Company:
https://www.linkedin.com/company/quantiphi
Seniority: Mid-Senior level
Industries: Data Infrastructure and Analytics and Information Services
Job details:
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.
● Strong 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.
Click on Apply to know more.
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