Generative AI/Machine Learning Engineer

SwiconGroup has been a leading member of the IT arena for almost 15 years and has been present in Romania since our wide range of services and highly trained professionals give us the opportunity to shape our solutions to fully meet the ideas and wishes of our clients. We are proud to have leading banks, insurance, and telecommunication companies, as well as large FMCG corporations and SSCs, amongst our highly prestigious partners.

BENEFITS:

• Salary: 11.000-13.000 ron net
• Meal tickets
• Medical Subscription
• Hybrid Work

RESPONSIBLITIES:

Accelerate GenAI & ML Adoption: Drive the adoption of Generative AI and Machine Learning technologies.

Use Case Validation & Reusability: Collaborate with the AI & Automation Product Owner to validate backlog priorities, assess technical feasibility, and determine whether existing ML or GenAI assets can be scaled or adapted for new use cases.

End-to-End Solution Delivery: Partner with cross-functional teams—including data scientists, ML/GenAI engineers, data/cloud experts, and RPA developers—to turn business problems into viable, sustainable solutions using ML algorithms or GenAI architectures (e.g., RAG, LLMs).

Stakeholder Engagement: Work directly with business stakeholders to understand their needs, translate them into solution requirements, and provide actionable recommendations that align with business strategy.

Model Development & Deployment: Design and build both predictive ML models and GenAI solutions—from data preprocessing and feature engineering to model development, fine-tuning, evaluation, and deployment—leveraging Azure, Databricks, and other enterprise platforms.

GenAI-Specific Capabilities: Architect and implement Retrieval-Augmented Generation (RAG) systems, fine-tune LLMs, and apply advanced prompt engineering techniques to build chat-based tools, search augmentation solutions, and virtual assistants that deliver real business value.

Performance Monitoring & Validation: Conduct rigorous model evaluation and performance monitoring for both ML and GenAI models to ensure reliability, fairness, and compliance.

JOB REQUIREMENTS (GenAI & ML Focus)

• Familiarity with Large Language Models (LLMs), prompt engineering, vector databases (e.g., FAISS, Pinecone), and Retrieval-Augmented Generation (RAG) architectures.
• Education: Bachelor’s Degree
• Experience: Typically 4–5 years of hands-on experience developing and deploying ML and/or GenAI solutions in a business context, ideally within sales, operations, or enterprise functions.
• Proficiency in Python for data manipulation, model development, and integration.
• Experience with PySpark and working in Databricks for scalable data pipelines and model training.
• Strong hands-on experience with Azure services (e.g., Azure Machine Learning, Azure AI Search, Azure OpenAI, Azure Functions, Azure Kubernetes Service).
• Experience with containerization and deployment frameworks like Docker, AKS, or serverless options.