QU
Full time
🤖 AI / ML
Architect - Machine Learning (MLOps Specialist) at Quantiphi
Listed by DevShelfHub
Mumbai / Bangalore
Hybrid
Senior · 7–11 yrs
About the Role
Quantiphi is hiring an Architect - Machine Learning (MLOps Specialist) in Mumbai or Bangalore to architect and implement production-grade ML and LLMOps pipelines on AWS cloud-native infrastructure.
This role owns model lifecycle management from training through registry, deployment, monitoring, and governance—with deep expertise in SageMaker, Kubeflow, MLflow, and LLMOps automation frameworks.
What you'll do
- Lead architecture and implementation of production MLOps and LLMOps infrastructure on AWS.
- Designing and implementing ML CI/CD pipelines with automated training, testing, validation, and endpoint deployment
- Building dynamic versioned pipelines using SageMaker Pipelines, Step Functions, or Kubeflow
- Managing feature engineering pipelines and Feature Store operations
- Implementing lineage tracking for training data snapshots, feature versions, and code versioning
- Supporting LLMOps pipelines including prompt versioning and evaluation automation
- Deploying and monitoring models with SageMaker Model Monitor and observability tooling
- Applying security best practices, IAM, secrets management, and artifact governance
- Transforming data using Snowflake, Databricks, Spark, or EMR
- Integrating Bedrock, OpenAI, Anthropic, or Llama models into production workflows
What we're looking for
- 8+ years in ML/AI engineering or MLOps roles with strong architecture exposure
- Strong expertise in AWS cloud-native ML stack: EKS, ECS, Lambda, API Gateway, CI/CD
- Hands-on experience with MLOps toolsets: MLflow, Kubeflow, SageMaker Pipelines, Airflow, BentoML, KServe, Seldon
- Deep understanding of model lifecycle management (training → registry → deployment → monitoring)
Skills & Technologies
Required
8+ years in ML/AI engineering or MLOps roles with strong architecture exposure
Strong expertise in AWS cloud-native ML stack: EKS, ECS, Lambda, API Gateway, CI/CD
Hands-on experience with MLOps toolsets: MLflow, Kubeflow, SageMaker Pipelines, Airflow, BentoML, KServe, Seldon
Deep understanding of model lifecycle management (training → registry → deployment → monitoring)
Experience implementing LLMOps pipelines with prompt versioning and evaluation metrics
Strong experience with AWS SageMaker (Training, Processing, Batch Transform, Pipelines, Feature Store, Model Registry, Model Monitor)
Experience implementing ML CI/CD pipelines with automated model promotion and endpoint deployment
Strong SQL and data transformation with Snowflake, Databricks, Spark, or EMR
Benefits & Perks
- Health Insurance
- Flexible Leave Policy
- Learning Budget
- EPF / NPS
Why This Role is Good for Experienced Professionals
- Shape enterprise MLOps and LLMOps standards on AWS SageMaker while leading architecture for model CI/CD, drift detection, feature stores, and Bedrock/OpenAI LLM pipelines.
- Architect AWS cloud-native ML stack on EKS, ECS, Lambda, and API Gateway
- Implement MLOps with MLflow, Kubeflow, SageMaker Pipelines, Airflow, BentoML, KServe, and Seldon
- Own model lifecycle: training, registry, deployment, monitoring, and governance
- Build LLMOps pipelines with prompt versioning, evaluation metrics, and automation frameworks
- Design dynamic versioned pipelines with SageMaker Pipelines, Step Functions, or Kubeflow
- Manage feature engineering pipelines and Feature Store (SageMaker or Feast)
- Implement lineage tracking for training data, feature versions, and reproducibility
- Work with Bedrock, OpenAI, Anthropic, or Llama models in production
- Apply CloudWatch, SageMaker Model Monitor, Prometheus/Grafana, or Datadog observability
- Strong foundation in Python, SQL, Snowflake, Databricks, Spark, and EMR data transformation
About Quantiphi
Quantiphi is an award-winning AI-first digital engineering company solving the toughest business problems with cutting-edge technologies. The Quantiphi family thrives in a culture built on transparency, diversity, integrity, learning, and growth across a hybrid global workforce.
- Industry
- Technology
- Company Size
- 500+
- Website
- quantiphi.com
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Job Details
- Type
- Full time
- Level
- Senior
- Experience
- 7–11 years
- Location
- Mumbai / Bangalore
- Work Mode
- Hybrid
- Category
- AI / ML
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