IA Engineer – Semi Senior Adv

Location: Argentina

What you’ll be doing?

As a IA Engineer at DinoCloud, you will contribute to the design, development, training, and deployment of Machine Learning models and Generative AI solutions, working with LLMs, RAG architectures, and agentic AI systems. The role focuses on implementing real business use cases while collaborating closely with senior profiles and evolving solutions under defined technical guidelines.

  • Implement and optimize Generative AI solutions based on Large Language Models (LLMs) for enterprise use cases.
  • Develop Retrieval-Augmented Generation (RAG) architectures, including:
    • Document ingestion and preprocessing
    • Chunking and embedding strategies
    • Information retrieval and response generation
  • Integrate LLMs with external tools, APIs, databases, vector stores, and knowledge bases.
  • Collaborate in the development of agentic AI systems, contributing to:
    • Multi-step reasoning
    • Tool usage
    • Workflow automation
  • Develop predictive models and Machine Learning algorithms aligned with specific business needs.
  • Execute experiments and benchmarks across models, embeddings, and retrieval techniques, following established technical guidelines.
  • Apply feature engineering techniques to improve model performance and data quality.
  • Collaborate on the implementation of training and validation pipelines.
  • Perform exploratory and advanced data analysis, applying statistical techniques to identify:
    • Patterns
    • Correlations
    • Anomalies
  • Work with data processing and manipulation frameworks on structured and semi-structured data.
  • Collaborate on the design and implementation of end-to-end pipelines for model training and deployment.
  • Participate in deployment automation and the adoption of MLOps best practices.
  • Implement and maintain monitoring and observability tools for deployed models and AI systems.
  • Produce clear and structured technical documentation for implemented solutions.
  • Work closely with senior engineers, product teams, and business stakeholders to translate requirements into technical solutions.
  • Provide technical support to other teams when required, under the guidance of technical leaders.

What would you need to succeed in this role?

  • Degree in Computer Science, Data Science, Systems Engineering, or equivalent professional experience.
  • Hands-on experience with Machine Learning and Artificial Intelligence, including:
    • LLMs and RAG architectures
    • NLP and/or Computer Vision
    • Deep Learning
    • Predictive modeling
  • Experience with data manipulation and processing frameworks.
  • Proficiency in Python, PyTorch, Jupyter, and basic knowledge of Apache Spark.
  • English level C1 (fluent reading and communication). A validation will be performed in the first step of the process.
It is a plus if you have:
  • AWS certifications related to data or AI (e.g., Data Engineer, AWS AI Practitioner).
  • Experience with Infrastructure as Code (Terraform and/or AWS CDK).
  • Basic knowledge of MLOps and cloud-based deployments.