Pineswift Technologies
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Gurugram · On-site · Oct 9
51 to 200 Employees · Gurgaon, India
Hiring: Engineering
What employees say
+ I don't like the culture of Pineswift. Earlier, when I joined this compay I was told that you will have to work 2 days from the Home & rest you have to work from the office, bu
− There is no good management for this company. I was working for the client called Airtel-Africa, but within 6 months of time I got laid off. Apart from Airtel-Africa, they don't ha
More reviews on the company profile.
Job description
Overview
We have a few requirements for ML Ops. PFB the details:
Responsibilities
- Partner with data scientists to package models and prepare them for production deployment
- Deploy models for batch scoring or real-time inference based on business requirements
- Develop production scoring and supporting data pipelines using Python and PySpark
- Automate deployment validation, versioning and release workflows
- Manage model artifacts, dependencies, configurations and deployment history
- Monitor model performance, data drift, scoring failures and operational reliability
- Implement alerts, troubleshooting procedures, rollback mechanisms and recovery processes
- Support approved model refreshes and redeployment in collaboration with model owners
- Work with technology, security and model-governance teams to meet enterprise requirements
- Maintain deployment documentation, monitoring controls and operational runbooks
Qualifications
- Strong hands-on proficiency in Python and PySpark
- Practical experience operationalizing and deploying machine-learning models.
- Sound modeling knowledge, including evaluation metrics, model behaviour, drift and performance interpretation
- Experience building production scoring pipelines and monitoring model operations
- Familiarity with model versioning and lifecycle-management tools
- Experience with CI/CD, automated testing and dependency management
- Ability to troubleshoot issues across data pipelines, model execution and deployment environments
- Working knowledge of the banking domain and the governance requirements associated with production models
- Experience with Databricks and Azure-based deployment environments
- Familiarity with APIs, containers and orchestration platforms
- Experience supporting model approvals, audit documentation and controlled releases
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Job application FAQ
Last updated 26 October 2026
- How do I apply for ML Ops-Model Deployment & Monitoring at Pineswift Technologies?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Pineswift Technologies may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this ML Ops-Model Deployment & Monitoring role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is ML Ops-Model Deployment & Monitoring remote or on-site in Gurugram, Haryana?
- This listing is marked on_site with location Gurugram, Haryana. Confirm details on the job description before applying.
- What skills matter for this ML Ops-Model Deployment & Monitoring role at Pineswift Technologies?
- Key skills for this role include skills listed in the job description. Upload a resume to see which requirements you already meet and which are gaps.