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Ryz Labs
Ryz Labs
11 – 50 Angajați
ConsultanțăLogisticăMarketing
Ryz Labs construiește startupuri de la zero și ajută companiile în creștere să își extindă operațiunile. Activă în domeniile consultanței, logisticii și marketingului, compania oferă soluții pentru atragerea talentelor tehnice, concepute pentru a sprijini afacerile emergente pe măsură ce dezvoltă produse, își consolidează echipele și concurează pe piețe aflate într-o evoluție rapidă.
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Principal Machine Learning Engineer - Ryz Labs (Remote in Argentina)

Lead production machine learning and scalable AI platform development for Ryz Labs’ international client. Own distributed architecture, MLOps, and security controls for LLM-powered systems.

ARArgentinaRemoteNormă întreagăLiderLimbă Obligatorie: englezăInginer de învățare automată
AWSAzureCloudDockerGoGoogle Cloud PlatformMicroserviciiPythonSisteme distribuiteTypeScript

Descriere

  • Deploy and operate AI models in production at scale.
  • Track model quality, hallucination rates, drift, latency, and infrastructure spending.
  • Architect distributed, event-driven microservices with Python, Go, or TypeScript.
  • Create infrastructure-as-code and CI/CD pipelines for reliable service delivery.
  • Establish agent permissions, human-review workflows, data isolation, and defenses against prompt injection.
  • Work with Product Managers from the outset to turn business needs into scalable technical designs.
  • Explain architectural trade-offs to executives and senior client stakeholders.
  • Help develop advanced AI platforms for an international client.
  • Act as a senior technical authority across production systems, applied AI, and engineering practices.

Cerințe

  • Bring 12–15+ years of software engineering experience, progressing from backend and distributed-systems architecture into production machine learning.
  • Demonstrate deep expertise in MLOps, model evaluation, advanced RAG, vector search using embeddings, HNSW, and hybrid retrieval, plus fine-tuning.
  • Master distributed systems, microservices, and asynchronous event-driven architectures using Python, Go, or TypeScript.
  • Have hands-on experience with Docker, AWS, Google Cloud or Azure, and automated CI/CD delivery.
  • Understand LLM safety, threat modeling, data-boundary enforcement, and agent security in practical environments.
  • Communicate fluently in English.
  • Explain complex technical decisions clearly to client executives and non-technical stakeholders.
  • Experience with multi-agent orchestration tools such as LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or MCP is desirable.
  • Background in consulting, technical advisory work, or high-growth technology platforms is desirable.

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