MLOps Engineer | AI-Powered Enterprise SaaS | AWS SageMaker, Bedrock, LLM Pipelines, RAG, CI/CD, Python, FastAPI, MLflow, DynamoDB
- 40K-50K
- Bengaluru, Hybrid
Full Job Description
Top 25 AI Company of 2024 and a 3x Great Place to Work – this is an enterprise SaaS powerhouse revolutionizing how the world plans, builds, and manages infrastructure. With $300B+ in capital programs trusted by 300+ customers and 40,000+ projects across transportation, healthcare, water & utilities, higher education, and government – the impact is real, the scale is massive. This is where AI meets infrastructure, and the brightest minds solve challenges that actually matter.
A skilled MLOps Engineer is needed to design, implement, and maintain scalable ML and LLM pipelines in cloud environments. This is a critical production role – owning reliability, efficiency, and performance of ML systems at scale, including RAG systems, auto-scaling APIs, and CI/CD automation on AWS.
What You’ll Do
- Design and maintain scalable ML and LLM pipelines on AWS
- Work hands-on with SageMaker, Lambda, Bedrock, Batch with Fargate
- Manage infrastructure components – RDS (PostgreSQL), DynamoDB, SQS, CloudWatch, API Gateway
- Automate CI/CD workflows for high-performance ML workloads
- Detect and mitigate data, concept, and label drift in production ML systems
- Provision and manage cloud resources supporting RAG systems
- Monitor model health using Evidently, NannyML, Phoenix, Grafana
- Drive model retraining pipelines via MLflow, Kubeflow, or Airflow
What You Bring
- 5+ years of hands-on experience with AWS services – Lambda, Bedrock, SageMaker, Fargate, DynamoDB, SQS, CloudWatch
- Proven expertise in drift analysis – data, concept & label drift in production
- Proficiency with REST API frameworks – FastAPI, Flask
- Solid understanding of ML frameworks – PyTorch, TensorFlow
- Familiarity with model observability and monitoring tools
- Experience with MLflow / Kubeflow / Airflow for retraining workflows
- Bonus: AWS Certified Machine Learning – Specialty
Education
- BE / B.Tech / ME / M.Tech in any Engineering discipline
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