About Position:

We are seeking a highly skilled Senior Machine Learning Engineer to own and enhance the product-sizing capability of a cloud-based, cloud-agnostic telecom analytics platform. The platform is designed to support consistent deployments across public, private, and hybrid cloud environments. This role blends machine learning, performance engineering, capacity planning, software development, and telemetry analytics to build accurate sizing models and optimize platform deployments. The ideal candidate will work closely with product, engineering, support, and customer teams to deliver scalable, data-driven solutions that improve infrastructure planning, resource utilization, and customer experience.

• Role: Senior ML Engineer
• Location: Pune
• Experience: 5 to 10 Years
• Job Type: Full Time Employment

What You'll Do:

• Design, implement, validate, and maintain sizing models for product components and end-to-end platform deployments.
• Model infrastructure requirements including CPU, memory, storage capacity, disk IOPS, throughput, network bandwidth, pod counts,



worker threads, Redis shards, and operational headroom based on customer workloads.
• Develop and improve data-driven sizing methodologies using statistical analysis and machine learning techniques.
• Support telecom workload dimensions such as PPS, EPS, OPS, protocol mix, call rates, active subscribers, concurrent sessions, recording volumes, retention periods, replication requirements, and high-availability topologies.
• Enhance existing regression-based sizing approaches using multivariate regression, clustering, time-series forecasting, nonlinear models, and other machine learning techniques where appropriate.
• Evaluate model performance using holdout datasets, cross-validation strategies, confidence intervals, prediction intervals, sensitivity analysis, and error metrics.
• Detect and investigate outliers, missing data, configuration drift, throttling, system saturation, and non-representa

📌 Senior Machine Learning Engineer (Pune)
🏢 Persistent Systems
📍 Pune