Machine Learning Engineer

• Work in a pair with an FDE and an FDX
• Build and ship production GenAI systems into customer environments
• Build and optimize RAG systems for production use cases
• Build the evaluation harness before building the feature
• Write production code across AI, backend services, and data pipelines
• Integrate AI components into backend services and RESTful APIs
• Deploy systems to AWS, or GCP/Azure where required by the customer, using containers and CI/CD
• Implement LLMOps and AgentOps practices, including agent tracing, prompt and version management, cost and latency monitoring, regression testing, and drift detection
• Contribute to enablement and handover through documentation, runbooks, and pairing with client engineers
• Feed reusable components and lessons back into Provectus Blueprints
• Participate in technical discussions and architectural decisions
• Conduct model evaluation and improve failure modes
• Optimize model performance, efficiency, and reliability
• Mentor junior and mid-level AI engineers
• Conduct code reviews and share knowledge through documentation, presentations, and workshops

Explore Senior AI/ML Engineer, GenAI, AWS at Provectus. Review requirements and application details.