Iris Software Hiring 2026 | Senior Machine Learning Engineer | Hybrid | Noida, Pune & Gurugram
Company Introduction
Iris Software is a leading global IT services and consulting company with over 35 years of industry experience. Trusted by several Fortune 500 companies, Iris Software specializes in Application Engineering, Data & Analytics, Cloud, DevOps, MLOps, Quality Engineering, and Business Automation. With more than 4,300 professionals across India, the USA, and Canada, the company delivers innovative technology solutions for industries including Banking, Capital Markets, Insurance, Investment Management, and Risk & Compliance. Iris Software fosters a culture of innovation, collaboration, and continuous learning, empowering employees to grow professionally while working on cutting-edge technologies.
Job Highlights
| Particulars | Details |
|---|---|
| Company | Iris Software |
| Position | Senior Machine Learning Engineer |
| Experience | 5–9 Years |
| Work Mode | Hybrid |
| Job Locations | Noida, Pune, Gurugram |
| Industry | IT Services & Consulting |
| Department | Data Science & Analytics |
| Employment Type | Full-Time, Permanent |
| Role Category | Data Science & Machine Learning |
| Notice Period | Immediate to Maximum 15 Days |
| Openings | 1 |
Role Overview
The Senior Machine Learning Engineer will be responsible for designing and optimizing scalable machine learning infrastructure, automating ML pipelines, deploying production-grade AI solutions, and implementing MLOps best practices. The role involves close collaboration with Data Scientists, Data Engineers, and DevOps teams to ensure reliable, efficient, and scalable machine learning systems.
Key Responsibilities
- Design and manage scalable ML infrastructure for model training, deployment, and monitoring.
- Build and automate end-to-end machine learning pipelines including data ingestion, training, validation, deployment, and monitoring.
- Implement CI/CD and Continuous Training (CT) pipelines for ML lifecycle automation.
- Ensure model reproducibility, versioning, and traceability using MLflow, DVC, Kubeflow, or similar tools.
- Monitor model drift, data quality, and production model performance.
- Collaborate with Data Science, Data Engineering, and DevOps teams to standardize ML workflows.
- Optimize ML infrastructure across AWS, Azure, and GCP environments.
- Maintain governance, compliance, documentation, and auditability of ML systems.
- Mentor junior engineers and contribute to technical strategy discussions.
Required Skills
Programming & Machine Learning
- Python
- TensorFlow
- PyTorch
- Scikit-learn
- Machine Learning Engineering
- Data Engineering
MLOps & Pipeline Tools
- Kubeflow
- MLflow
- TensorFlow Extended (TFX)
- Kubeflow Pipelines
- DVC
- SageMaker
Cloud Technologies
- Amazon Web Services (AWS)
- Microsoft Azure
- Google Cloud Platform (GCP)
DevOps & Deployment
- Docker
- Kubernetes
- Jenkins
- GitLab CI/CD
- CircleCI
- Continuous Integration / Continuous Deployment (CI/CD)
Big Data
- PySpark
Eligibility Criteria
- 5–8 years of experience in Machine Learning Engineering or related roles.
- Strong programming skills in Python.
- Hands-on experience with TensorFlow, PyTorch, and Scikit-learn.
- Practical knowledge of MLOps frameworks such as Kubeflow, MLflow, and TFX.
- Experience deploying machine learning models on AWS, Azure, or GCP.
- Expertise in Docker, Kubernetes, and CI/CD pipelines.
- Strong understanding of scalable ML infrastructure and production deployment.
Educational Qualification
| Qualification | Eligibility |
|---|---|
| Any Graduate | Eligible |
| B.Tech / B.E. | Eligible |
| B.Sc. | Eligible |
| BCA | Eligible |
| B.Com | Eligible |
| BBA / BMS | Eligible |
| Diploma | Eligible |
| B.Arch | Eligible |
| B.Ed. | Eligible |
How to Apply
Interested candidates can share their updated resume to:
📧 kanika.singh@irissoftware.com
WhatsApp: 9315758843
You can also connect with the recruiter through LinkedIn for further details.
Why Join Iris Software?
- ✔ Work with Fortune 500 global clients.
- ✔ Hybrid work model for better flexibility.
- ✔ Exposure to cutting-edge AI, Machine Learning, Cloud, and MLOps technologies.
- ✔ Opportunity to work on large-scale enterprise applications.
- ✔ Learning-driven culture with strong career growth opportunities.
- ✔ Collaborative and innovation-focused work environment.
Important Note
Candidates with an immediate joining availability or a notice period of up to 15 days will be preferred. Applicants should possess strong expertise in Machine Learning Engineering, MLOps, Cloud Platforms, CI/CD, Docker, Kubernetes, and Python to successfully deliver scalable, production-grade AI solutions.
