Smartsheet12 days ago
Senior AI/ML Operations Engineer
Salary not specified
MARKET
15,900 ₽median for this role
Data Scientist · 115 jobs with disclosed pay
5,000half of the offers: 12,796–20,50043,793
The employer didn't disclose pay — compare with the market yourself.
Bangalore
Responsibilities
- 01Designing, developing and maintaining stable and reliable AI/ML Ops platforms/pipelines
- 02Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
- 03Design and implement automated CI/CD pipelines to accelerate model deployment using tools
- 04Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
- 05Implement post-deployment monitoring for model performance, data drift, and latency using tools
- 06Automate retraining and data pipeline workflows to ensure models stay accurate over time
- 07Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks
- 08Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
- 09Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production
- 10Manage versioning for data, code, and models using tools like MLflow
- 11Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
- 12Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation's data infrastructure
- 13Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
Requirements
- 01Enterprise SaaS software solutions with high availability and scalability
- 02Solution handling large scale structured and unstructured data from varied data sources
- 03Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
- 04In depth experience in AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
- 05AI/MLOps workflows on Databricks, MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
- 06Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
- 07Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP)
- 08Programming languages like Python and SQL
- 09Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
- 10Solution Cost Optimisations and design to cost
- 11Legally eligible to work in India on an ongoing basis
What we offer
- 01Remote work
- 02Equal Opportunity Employer