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Accenture

Advises businesses and runs their technology

Senior Engineer - LLM Optimization & Adaptation

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeAthens, GreeceNo salary listed

About the Job

Requirements

  • A B.Sc., M.Sc., or equivalent experience in Computer Science, Engineering, AI, Data Science, Machine Learning, or a related field.
  • Strong Python skills and hands-on experience in machine learning and large language model engineering and production-grade AI experimentation.
  • Good understanding of large language models, small language models, open-weight models, model families, context windows, token economics, latency, accuracy, and cost trade-offs.
  • Experience with model evaluation, benchmarking, test sets, quality metrics, regression testing, and human evaluation workflows.
  • Hands-on exposure to fine-tuning, LoRA, parameter-efficient fine-tuning, prompt optimization, retrieval optimization, or model adaptation techniques.
  • Familiarity with retrieval-augmented generation, GraphRAG, embeddings, vector search, and retrieval quality improvement.
  • Experience with MLflow, Weights & Biases, LangSmith, Langfuse, or similar experiment tracking and observability tools.
  • Comfort working with engineering teams to translate model insights into production-ready AI patterns.

Responsibilities

  • Develop model evaluation and benchmarking frameworks for large language model, small language model, and agentic AI use cases.
  • Recommend model selections based on accuracy, latency, cost, safety, explainability, and operational constraints.
  • Conduct fine-tuning, LoRA, parameter-efficient fine-tuning, prompt optimization, and retrieval optimization experiments for priority business use cases.
  • Develop distillation and model-compression proof points where smaller or more efficient models can deliver sufficient performance.
  • Build evaluation datasets, test harnesses, golden-answer sets, and regression-testing routines for AI applications.
  • Develop observability dashboards and quality feedback loops covering model performance, hallucination risk, drift, cost, and user feedback.
  • Define target-state patterns for open-weight or self-hosted large language model adoption, including architecture, governance, and operational-readiness considerations.

Desired Qualifications

  • Experience with Hugging Face, PyTorch, Transformers, quantization, model compression, or distillation.
  • Awareness of self-hosted or open-weight large language model architecture, deployment, monitoring, and governance considerations.
  • Experience with Azure AI Foundry, Azure Machine Learning, Databricks, or enterprise AI platforms.
  • Understanding of regulated environments, model risk, responsible AI, data privacy, and banking compliance requirements.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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