ML OPS - Senior Engineer

Iris Software; Dadri; On-site; INR 2,800,000 - 4,800,000; Full time

Job summary

Iris Software in Noida, UP, India, is seeking a Senior ML Ops Engineer to lead AWS-based delivery initiatives, architect cloud solutions, and mentor offshore teams. You will drive automation, collaborate with AI/ML engineers, and ensure secure, scalable cloud workloads.

The role requires deep AWS expertise, containerization skills, and strong ownership with client-facing experience, across distributed working hours.

Qualifications

• 5+ years of hands-on experience delivering AWS projects, with overall 10+ years of experience.
• Deep understanding of core AWS services (IAM, VPC, ECS/EKS, Lambda, S3, RDS, Sagemaker etc.)
• Strong expertise in container technologies (Docker) and container orchestration (Kubernetes/EKS)
• Proven experience with Infrastructure as Code (AWS CDK preferred; Terraform acceptable)
• Hands‑on experience with GitHub Actions and CI/CD workflow automation

Responsibilities

• Lead and oversee multiple AWS-based delivery initiatives in parallel
• Act as the primary technical point of contact for client stakeholders
• Architect and guide cloud solutions leveraging AWS best practices
• Mentor offshore teams, ensuring progress during distributed working hours
• Proactively identify risks, dependencies, and bottlenecks; unblock teams effectively
• Drive infrastructure automation and platform maturity
• Collaborate with AI/ML engineers to support ML infrastructure, pipelines, and deployments
• Ensure security, reliability, scalability, and cost-awareness across cloud workloads

Skills

AWS

Docker

Kubernetes

CI/CD

GitHub Actions

Python

MLOps

Client communication

Ownership mindset

Tools

Terraform

AWS CDK

Job description

ML OPS - Senior Engineer

Location: Noida, UP, India

Key Responsibilities

• Lead and oversee multiple AWS-based delivery initiatives in parallel
• Act as the primary technical point of contact for client stakeholders
• Architect and guide cloud solutions leveraging AWS best practices
• Mentor and enable offshore teams, ensuring progress during distributed working hours
• Proactively identify risks, dependencies, and bottlenecks; unblock teams effectively
• Drive infrastructure automation and platform maturity
• Collaborate with AI/ML engineers to support ML infrastructure, pipelines, and deployments
• Ensure security, reliability, scalability, and cost-awareness across cloud workloads

Required Skills Experience

• 5+ years of hands‑on experience delivering AWS projects, with overall 10+ years of experience
• Deep understanding of core AWS services (IAM, VPC, ECS/EKS, Lambda, S3, RDS, Sagemaker etc.)
• Strong expertise in container technologies (Docker) and container orchestration (Kubernetes/EKS)
• Proven experience with Infrastructure as Code (AWS CDK preferred; Terraform acceptable)
• Hands‑on experience with GitHub Actions and CI/CD workflow automation
• Understanding of the AI/ML ecosystem, including model deployment and ML infrastructure patterns
• Experience owning client communication, technical discussions, and delivery updates
• Ability to support and unblock teams during offshore working hours
• Self‑driven, proactive, and accountable with a strong ownership mindset

Nice to Have

• Experience with MLOps platforms and ML pipelines
• Exposure to cloud cost optimization and FinOps practices
• Prior people‑management or delivery‑lead experience

Mandatory Competencies

• Data AI - MLOPS - CI/CD (for ML pipelines)
• Data AI - MLOPS - Data Pipeline Feature Management
• Data AI - MLOPS - Model Registry Experiment Tracking
• DevOps/Configuration Mgmt - DevOps/Configuration Mgmt - Containerization (Docker, Kubernetes)
• Data AI - MLOPS - Python
• Data AI - MLOPS - Machine Learning (ML)