обновлено 5 дней назад
Senior Machine Learning Engineer (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Machine Learning Engineer (AI): Building and operationalizing scalable LLM-powered backend systems and MLOps pipelines with an accent on RAG architectures, vector databases, and high-throughput API design. Focus on orchestrating complex LLM workflows, ensuring model observability, and optimizing performance for production-grade AI applications.
Location: Must be based in Brazil or Argentina
is a software development company providing digital transformation services and AI-powered solutions for various industries.
What you will do
- Build and refine ML Engineering platforms, backend systems, and microservices using FastAPI.
- Deploy and operationalize LLM and Generative AI models with robust MLOps practices.
- Orchestrate model pipelines including feature engineering, inference, and continuous training.
- Implement LLM observability, prompt management, and cost optimization strategies.
- Collaborate with cross-functional teams to gather requirements and deliver production-ready code.
Requirements
- Location: Must be based in Brazil or Argentina.
- 7+ years of strong Python coding experience.
- 2+ years of hands-on experience with machine learning and production LLM systems.
- 3+ years of experience building backend APIs with FastAPI, async patterns, and SQLAlchemy.
- Strong understanding of RAG architectures, vector databases, and LLM orchestration tools like LangChain/LangGraph.
- Experience with MLOps tools (MLflow) and cloud platforms (Azure preferred).
Nice to have
- Experience with DevOps practices (Docker, Kubernetes, CI/CD).
- Knowledge of data engineering and Big Data systems.
- Domain expertise in regulated industries like healthcare or pharma.
- Experience with document processing and OCR tooling.
Culture & Benefits
- Flexible working hours and remote-friendly environment.
- Access to Udemy courses for continuous learning.
- Regular team-building events, workshops, and knowledge-sharing sessions.
- Clear career progression paths.
- Paid absence days to support work-life balance.
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