Senior MLOps Engineer | AI-Powered Enterprise Software

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 Youll 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