
Transformative AI Expert
5 days ago
As part of our mission to drive a transformation from leading supplier of trucks, buses, and engines to providing complete and sustainable transport solutions, we are looking for an experienced AI Engineer to join our team.
The OpportunityBy democratizing access to knowledge and artificial intelligence, we can foster a transition towards a sustainable transport system. Our current initiatives leverage AI for productivity gains and to transform our processes or create new business opportunities across Scania Nederland B.V. and TRATON.
Responsibilities- Technical leadership in developing and deploying the Generative AI platform.
- Strategic contributions to the roadmap for the Generative AI area, working closely with the team.
- Building, testing, and deploying AI models, either from scratch or using the existing platform.
- Statistical analysis and interpretation to optimize AI model performance and systems.
- Development of self-service Generative AI services.
- Supporting the implementation of LLMOps within the team.
- Contributing to setting AI best practices and methodologies.
- Collaboration with cross-functional teams to identify business needs and develop valuable solutions.
Qualifications and Requirements
- Proficiency in understanding Transformer Architectures (BERT, GPT, T5 etc), Named Entity Recognition (NER) using Spacy Models, and libraries like NLTK, Langchain Loaders, Sentiment Analysis, Topic Modeling, Text Summarization.
- Expertise in creating optimized RAG applications: Dense Retrieval mechanisms, Sparse Retrieval, Hybrid Retrieval, Embedding Techniques, Vector Databases, Query Understanding and Expansion, Context-Aware Retrieval, Evaluation Metrics, Prompts, Optimizers.
- Experience with fine-tuning mechanisms, including familiarity with the latest models such as GPT-3.5/4/4o, LLAMA, and Domain-Specific Fine-Tuning.
- Ability to build self-supervised corpora, Q&A pair templates, RHLF, prompt engineering templates.
- Background in Data Collection and Curation, Preprocessing, Exploratory Data Analysis (EDA), Feature Engineering, Data Augmentation and noise removal Techniques, and familiarity with Large-Scale Datasets, Data Lakes.
- Experience in Model Versioning, Experiment Tracking, CI/CD for ML, Monitoring and Logging, Reproducibility and Provenance, Containerization, Orchestration.
- Familiarity with Multi-Agent AI frameworks and agentic patterns.
Preferred Programming Languages and Tools
- Python.
- PyTorch/TensorFlow.
- Transformers.
- Git.
- Docker.
- SQL.
Our company culture encourages collaboration and innovation.
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