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LLM/GenAI engineer

AI/ML Computational Science Team Lead/Consultant | Mid-Level | Full time
Job No. R00218788 | Vilnius
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Apply for a highly demanded new age job – a Data Scientist/ GenAI LLM Engineer. Be part of Accenture team working in Lithuania and delivering projects to world leaders in various fields, like TV & Entertainment, Telecommunication, Finances, Insurance, Industry, Logistic & Supply Chain, and others.  

Working at the edge of AI/ML technologies we help our clients to leverage the value of unstructured data, to uncover the hidden power of accumulated enterprise information.

As an LLM engineer, you will have the opportunity to apply your deep expertise in LLM/GenAI technologies. Your main responsibility will be collaborating closely with clients to prototype, build, test, and deploy products powered by GenAI/LLM technology on a large scale. Additionally, you will play a key role in fine-tuning the hyperparameters of LLM models, optimizing their configuration to ensure the overall model performance and enhance the overall model performance to drive positive outcomes for clients. 

Benefits:

  • Competitive salary 2600 - 5000 EUR gross
  • Flexible vacation + health & travel insurance + relocation
  • Hybrid work model: flexible hours with the possibility to combine office and remote work.
  • Work with Fortune 500 companies from different industries all over the world
  • Skills development and training opportunities, company-paid certifications
  • Opportunities to advance career
  • An open-minded and inclusive company culture 

Key responsibilities:

  • Work with Python, LLM/GenAI frameworks and tools AI/ML end-to-end solutions developing
  • CI/CD pipelines development, LLM model containerizing and deployment on cloud or premise. Models testing and follow-up maintenance. All stages of ML model life cycle ensuring and support.
  • Design prototypes and POCs to demonstrate solution feasibility and value. Provide architecture solution.
  • Research, design, build, and train innovative applications of LLMs to solve complex real-world problems.
  • Provide technical guidance to clients adopting LLM technologies.

Required Qualifications:

  • Bachelor’s Degree (might be final course student) in Statistics, Applied Mathematics, Computer Science, or other related fields
  • 3+ years of hands-on Python development experience; 2+ years building and maintaining production APIs (FastAPI, Flask); strong software engineering fundamentals including testing, version control, and code quality
  • 2+ years with AI/ML/NLP/LLM technologies; 1+ year production experience with LLM APIs (OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI); hands-on experience with LLM frameworks (LangChain or similar); proficiency in prompt engineering, RAG implementation, and vector databases
  • 2+ years with cloud platforms (AWS, GCP, or Azure); 2+ years of experience with LLMOps/MLOps, model evaluation, CI/CD pipeline development, containerization, model deployment in test and production environments, familiarity with LLM observability tools
  • Be a team player, fluent in English and ability to clearly communicate complex LLM capabilities and limitations to non-technical stakeholders.
  • Due to project requirements, candidates must currently hold EU work permit and be available to start within 1 to 3 months of receiving an offer.

 

Desired Qualifications:

  • M.Sc. or Ph.D. in Computer Science, AI/ML, or related field
  • Experience with fine-tuning techniques (LoRA, QLoRA, PEFT), quantization, and model optimization; hands-on with open-source models (Llama, Phi, Gemma) and frameworks (HuggingFace Transformers, vLLM)
  • Proficiency with additional languages (Bash, TypeScript); experience with data platforms (Databricks, Snowflake); knowledge of graph databases (Neo4j) for advanced RAG
  • Expertise in agentic frameworks (LangGraph, AutoGen, Semantic Kernel), multi-agent systems, tool use/function calling, and complex orchestration patterns
  • Strong understanding of Responsible AI, including bias detection, guardrails implementation, content safety, data privacy, and AI governance; applied research experience in NLP/LLM domains

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