AI ML Ops Software Engineer (Bangalore Hybrid)

🏢 Smartsheet · 📍 Bangalore, INDIA · 💼 hybrid

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Position Summary & Responsibilities

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day.

Job Description/ Responsibilities:

Designing, developing and maintaining stable and reliable AI/ML Ops platforms / pipelines
Minimum experience of 4-6 Years required in AI ML Ops
Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stabili

🎯 Candidate Preparation Guide For Smartsheet Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Evaluating enterprise SaaS go-to-market acumen, user adoption strategies, and collaborative workflow optimization expertise.

📋 Preparation Priorities (Key Areas to Clarify):

1. Transactional sales mindset rather than long-term value creation
2. Superficial knowledge of enterprise workflow automation
3. Poor collaboration skills during cross-functional case study presentations

✨ Recommended Role Alignment Hook:

I drive enterprise SaaS adoption by turning complex workflow challenges into streamlined, collaborative operational wins.

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