Machine Learning Engineer

Persistent Systems; Pune District; Hybrid; INR 2,500,000 - 4,000,000; Full time

Benefits offered by this job

Hybrid work model

Flexible hours

Learning & development support

Job summary

Persistent Systems is seeking an experienced R&D Developer to join a team building an end-to-end ML platform powering network analytics anomaly detection. You will design training pipelines, manage orchestration on Kubernetes, and develop a Streamlit control panel for ML lifecycle configuration and deployment.

The role combines ML engineering with platform work including model versioning, ONNX export, and drift metrics visualization, with hybrid work options and a competitive salary.

Qualifications

• Experience building ML training pipelines and MLOps platforms.
• Experience with LSTM or recurrent networks for time-series modeling.
• Familiarity with anomaly detection in time-series data and model evaluation.
• Experience deploying models with ONNX and managing model artefacts.

Responsibilities

• Develop ML training pipelines for time-series data ingestion and model training.
• Maintain the orchestration layer to deploy and manage models across environments.
• Build UI surfaces (Streamlit) for ML lifecycle configuration, training, deployment, and drift monitoring.
• Write tests for training pipelines, APIs, and UI logic.
• Package components as Docker images and contribute to Kubernetes/Helm deployments.
• Collaborate with inference teams on model artefacts (ONNX) and metadata.

Skills

Python 3.11

Async Python

FastAPI

Pydantic

PyTorch

Argo Workflows

Kubernetes

Streamlit

MLflow

ONNX

Education

Bachelor's or Master’s degree in Computer Science / Data Science

Tools

Docker

Poetry

pip

Hera Python SDK

Job description

We are looking for an R&D Developer to join the team responsible for the end-to-end machine learning platform that powers our network analytics anomaly detection capability. The platform spans three interconnected components: a training pipeline that ingests time-series data, trains deep learning and clustering models, and exports them for production serving; an orchestration service that manages the full ML application lifecycle on Kubernetes; and a web-based control panel that gives operations and client-facing teams a unified interface to configure, train, deploy, and monitor models.

• Location: All Persistent Location
• Experience: 6 to 12 years
• Job Type: Full-Time Employment

What You'll Do:

• The role combines applied machine learning engineering with MLOps platform work.
• You will write training code that directly affects production model quality, maintain the orchestration layer that deploys and manages those models across environments, and develop the UI surface through which non-technical users interact with the ML lifecycle.
• Design, implement, and maintain ML training pipelines: data ingestion from columnar databases, dataset preparation, LSTM-based anomaly detection model training, and KMeans-based classifier training.
• Log, version, and register trained models using ML flow; export models to ONNX format for downstream inference deployment.
• Maintain the Fast API-based orchestration service: per-application YAML configuration storage and update, REST API endpoints for workflow lifecycle management, drift metrics exposure, and config artefact generation.
• Integrate with Argo Workflows (via the Hera Python SDK) to trigger, monitor, and manage distributed ML training jobs on Kubernetes.
• Manage Helm release deployment and teardown via Ansible Runner, including programmatic chart parameterization from application configuration.
• Build and maintain the Streamlit-based ML control panel: screens for application configuration, model training initiation, deployment management, retraining triggers, and drift metrics visualization.
• Implement interactive time-series drift charts and tabular workflow status displays within the control panel UI.
• Write and maintain unit and integration tests for training pipelines, orchestration API endpoints, and UI logic.
• Package all components as Docker images; contribute to Kubernetes and Helm deployment configurations.
• Collaborate with inference service teams on the model artefact contract (ONNX format, metadata, versioning).
• Participate in code reviews, architecture discussions, and maintain technical documentation.

Expertise You'll Bring:

• Proficiency in Python 3.11
• Experience structuring batch workflow scripts and packaging them for production execution (Docker, Poetry, pip)
• Familiarity with async Python and framework-level dependency injection (Fast API/Pydantic patterns)
• Strong understanding of type annotations, data validation with Pydantic, and clean API design
• Hands-on experience training LSTM or other recurrent neural networks for time-series tasks using PyTorch
• Understanding of anomaly detection approaches: reconstruction-based, threshold-based, and statistical methods applied to time-series data
• Working knowledge of clustering algorithms (KMeans and variants) and their use in classification or segmentation tasks
• Ability to evaluate model quality, tune hyperparameters, and interpret results on time-series datasets
• Bachelor’s or master’s degree in computer science, Data Science, Mathematics, or equivalent practical experience in machine learning engineering or MLOps platform development.
• Competitive salary and benefits package
• Culture focused on talent development with quarterly growth opportunities and company-sponsored higher education and certifications
• Opportunity to work with cutting-edge technologies
• Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards
• Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents

Values-Driven, People-Centric & Inclusive Work Environment:

Persistent is dedicated to fostering diversity and inclusion in the workplace. We invite applications from all qualified individuals, including those with disabilities, and regardless of gender or gender preference. We welcome diverse candidates from all backgrounds.

• We support hybrid work and flexible hours to fit diverse lifestyles.
• Our office is accessibility-friendly, with ergonomic setups and assistive technologies to support employees with physical disabilities.
• If you are a person with disabilities and have specific requirements, please inform us during the application process or at any time during your employment

“Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind.”