Scania Nederland B.V. Innovator
5 days ago
At Scania Nederland B.V., we are driving a transformation from leading supplier of trucks, buses, and engines to providing complete and sustainable transport solutions.
Our MissionWe aim to accelerate the shift by democratizing access to knowledge and artificial intelligence, fostering a transition towards a sustainable transport system.
The RoleIn this rapidly evolving team, we are seeking an experienced AI Engineer to help lead our mission to democratize access to knowledge and artificial intelligence capabilities, transforming how information is consumed, analyzed, utilized and knowledge generated.
Key Responsibilities- Lead and contribute to the technical development of the Generative AI platform.
- Contribute towards the strategy and roadmap for the Generative AI area, together with the team.
- Build, test, and deploy AI models from scratch or using the existing platform.
- Conduct statistical analysis and interpret results to optimize AI model performance and systems.
- Develop self-service Generative AI services.
- Support LLMOps implementation within the team.
- Support and contribute to setting AI best practices and methodologies.
- Work closely with cross-functional teams to capture business needs and develop valuable solutions.
Mandatory Skills and Qualifications
- Understanding of 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.
- Experience in creating optimized RAG applications: Dense Retrieval mechanisms (e.g., DPR, ColBERT), Sparse Retrieval (BM25, TF-IDF etc.), Hybrid Retrieval (HyDE), Embedding Techniques and retrievers, Vector Databases (Faiss, Pinecone, others), Query Understanding and Expansion (Chain of Thoughts, Tree-of-Thoughts, etc.), Context-Aware Retrieval, Evaluation Metrics (Relevance, Factual Accuracy, Coherence, Diversity, Perplexity etc), Prompts (e.g., QuestionAnswerPrompt, RefinePrompt), Optimizers (e.g., OptimizerChain).
- Experience with fine-tuning mechanisms.
- Familiarity with the latest models such as GPT-3.5/4/4o, LLAMA, and Domain-Specific Fine-Tuning.
- Experience in building self-supervised corpora, Q&A pair templates, RHLF, prompt engineering templates.
- Data Collection and Curation, Preprocessing, Exploratory Data Analysis (EDA), Feature Engineering, Data Augmentation and noise removal Techniques, familiarity with Large-Scale Datasets, Data Lakes.
- Model Versioning, Experiment Tracking (Mlflow/Kubeflow, Weights & Biases), CI/CD for ML, Monitoring and Logging, Reproducibility and Provenance, Containerization (Docker), Orchestration (Kubernetes).
- Familiarity with Multi-Agent AI frameworks and agentic patterns.
Programming & Tools
- Python.
- PyTorch/TensorFlow.
- Transformers.
- Git.
- Docker.
- SQL.
Good to Have
- Knowledge about Cloud Platforms (AWS, Azure), Model Serving (Flask, FastAPI), Model Compression.
- Knowledge and familiarity with Traditional machine learning.
Our company supports your career growth both locally and internationally through a structured development plan and courses.
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