Computer Science Engineer

The employer is looking for a:

Technical & AI research Leader (reported profession)

Tasks:
Technical strategy & model R&D leader:

• Technical Leader in the specialized development of SLMs (Small Language Models)
• Leader and responsible for the design of synthetic data pipelines for data extraction from large unstructured sources, enabling rapid interaction during the project fine-tuning phase
• Responsible for promoting continuous evaluation and improvement systems to measure and improve the reliability of created models and the use of implemented tools

Agentic systems & Rag Architecture:

• Owner of the Agentic-RAG platform from creation to context and error management
• Design tools with outputs generated by structured validation levels
• Create production workflows that combine OCR, multi-modals LLMs (Large Language Models) for the understanding and extraction of complex information and data from documents

Engineering Leadership & Platform:

• Responsible for leading and expanding the engineering organization (software + ML)
• Leader in building enterprise-level microservices architecture through the use of Python, Kubernetes, GraphQL, and appropriate data storage systems
• Responsible for defining production standards: CI/CD automation, distributed logging, testing frameworks, and SLO-based reliability
• Owner in the implementation of infrastructures that support the needs and requirements of local private enterprises, implementing solutions with solid security and control

Product & Customer Collaboration leader:

• Technical executive responsible for major clients during the implementation unlocking phases and subsequently in product adoption, also promoting the “drive product-market fit” through the implementation of rapid prototypes based on feedback obtained from the customer
• Responsible and Leader in collaboration between product teams for the translation of complex documents and information for the extraction of solutions at scale

Skills and technical specifics:

• Proven experience in the creation and deployment of SLMs with a focus on tool-calling, specialized and structured outputs, and fine-tuning (LoRA, post-training pipelines, AI document systems, OCR pipelines)
• Solid practical experience with Agentic-RAG systems in the design and experimentation phase, in synthetic data processing, and in generating high-quality data from unstructured and unorganized sources
• Consolidated experience in the production of ML infrastructure and tools (including low/no-code interfaces), with subsequent monitoring and evaluation (LayoutLM, Llama, multi-modal models, Text-to-SQL and query systems, creation of NL-SQL engines with visualization capabilities)
• Active learning systems leader: implementation of active cycles of models that learn directly from corrections requested by customers
• Solid engineering foundations and knowledge of: Python microservices, Kubernetes, Docker, GraphQL, PostgreSQL, C/C++, PyTorch, TensorFlow, Azure/AWS, CI/CD pipelines, Kafka, ElasticSearch, REST APIs, Testing & Quality: PyTest, automated testing frameworks
• Consolidated leadership through the management of a team of collaborators, engineers, and experts with the ability to establish technical and design standards, promoting rapid internal organizational growth in various experimentation and implementation phases