Principal ML Engineer

This is a fully remote position, open to applicants in Argentina.

📋 Description

• Deploy and oversee AI models at scale.

• Track model performance, including hallucination rates, drift, latency, and infrastructure expenses.

• Create distributed, event-driven microservices utilizing Python, Go, or TypeScript.

• Develop infrastructure-as-code and CI/CD pipelines to deliver services.

• Establish agent permission frameworks, human-in-the-loop processes, data isolation parameters, and prompt injection safeguards.

• Collaborate with Product Managers from the beginning to convert business needs into scalable architectures.

• Communicate architectural trade-offs to executives and key client stakeholders.

• Help shape the next generation of AI platforms for a global clientele.

• Act as a reliable technical authority across production systems, applied AI, and engineering excellence.

⛳️ Requirements

• 12–15+ years of experience in software engineering, demonstrating a clear progression from Backend/Distributed Systems Architecture to applied Production ML Engineering.

• Extensive experience with MLOps, model evaluation frameworks, advanced RAG, vector search (embeddings, HNSW, hybrid search), and fine-tuning.

• Strong expertise in distributed systems, microservices, and asynchronous event-driven patterns using Python, Go, or TypeScript.

• Practical knowledge of Docker, cloud infrastructure (AWS/GCP/Azure), and automated CI/CD pipelines.

• Familiarity with LLM safety, threat modeling, data boundary enforcement, and agent security.

• Proficient in English.

• Capability to clearly explain complex technical trade-offs to client executives and non-technical stakeholders.

• Previous experience with multi-agent orchestration frameworks (e.g., LlamaIndex, Semantic Kernel, AutoGen, CrewAI, MCP) is a plus.

• Experience in dynamic consulting, advisory roles, or rapidly growing tech platforms is a plus.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Opportunities for professional development and continuous learning.

• Flexible work arrangements and a supportive work environment.

• Health and wellness programs to support employee well-being.