Sr Machine Learning Ops Engineer

ThoughtFocus is seeking a Senior ML Systems Engineer contractor to bridge the gap between model development and production. The role focuses on building high-throughput pipelines for processing historical documents and transforming ML prototypes into scalable production systems on AWS infrastructure.

Responsibilities:

• Build and maintain scalable data pipelines that execute agentic workflows for entity extraction
• Deploy and manage infrastructure for both open-source LLMs (on EC2) and third-party APIs, focusing on maximum throughput and reliability
• Continuously optimize pipelines for unit cost and processing speed without compromising data integrity
• Act as a primary engineering contact for the Data Science team, operationalizing their trained models and prompt logic
• Implement advanced monitoring, alerting, and automated error-handling/retry logic for complex ML workflows
• Manage the AWS ecosystem (EC2, Lambda, S3, IAM) supporting the ML lifecycle

Requirements:

• Advanced proficiency in building robust, multi-threaded, or asynchronous applications in Python (Systems Level)
• Proficiency with Terraform or similar tools (e.g., Pulumi, CloudFormation) for provisioning and managing modular, version-controlled AWS infrastructure
• Deep expertise in EC2 Auto Scaling Groups, Lambda orchestration, and S3 data lakes
• Experience building autonomous AI workflows using AWS Agent Core or similar frameworks
• Proven track record in production monitoring (CloudWatch), logging, and troubleshooting distributed systems
• Strong grasp of AWS IAM for secure resource management
• Able to work during US business hours for collaboration and production support
• Experience with CI/CD for ML, containerization (Docker), and automated testing of data pipelines
• Experience with OCR or document digitization at scale
• Experience managing rate limits and costs across multiple LLM providers