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Mobileum is a leading provider of Telecom analytics solutions for roaming, core network, security, risk management, domestic and international connectivity testing, and customer intelligence.
More than 1,000 customers rely on its Active Intelligence platform, which provides advanced analytics solutions, allowing customers to connect deep network and operational intelligence with real-time actions that increase revenue, improve customer experience, and reduce costs.
Headquartered in Silicon Valley, Mobileum has global offices in Australia, Dubai, Germany, Greece, India, Portugal, Singapore and UK with global HC of over 1800+.
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At Mobileum we recognize that our team is the main reason for our success. What does work with us mean? Opportunities!
Role: GenAI/LLM Engineer – Domain-Specific AI Solutions (Telecom)
About the Job
We are seeking a highly skilled GenAI/LLM Engineer to design, fine-tune, and operationalize Large Language Models (LLMs) for telecom business applications. This role will be instrumental in building domain-specific GenAI solutions, including the development of domain-specific LLMs, to transform telecom operational processes, customer interactions, and internal decision-making workflows.
Roles & Responsibility:
- Build domain-specific LLMs by curating domain-relevant datasets and training/fine-tuning LLMs tailored for telecom use cases.
- Fine-tune pre-trained LLMs (e.g., GPT, Llama, Mistral) using telecom-specific datasets to improve task accuracy and relevance.
- Design and implement prompt engineering frameworks, optimize prompt construction and context strategies for telco-specific queries and processes.
- Develop Retrieval-Augmented Generation (RAG) pipelines integrated with vector databases (e.g., FAISS, Pinecone) to enhance LLM performance on internal knowledge.
- Build multi-agent LLM pipelines using orchestration tools (LangChain, LlamaIndex) to support complex telecom workflows.
- Collaborate cross-functionally with data engineers, product teams, and domain experts to translate telecom business logic into GenAI workflows.
- Conduct systematic model evaluation focused on minimizing hallucinations, improving domain-specific accuracy, and tracking performance improvements on business KPIs.
- Contribute to the development of internal reusable GenAI modules, coding standards, and best practices documentation.
Desired Profile
- Familiarity with multi-modal LLMs (text + tabular/time-series).
- Experience with OpenAI function calling, LangGraph, or agent-based orchestration.
- Exposure to telecom datasets (e.g., call records, customer tickets, network logs).
- Experience with low-latency inference optimization (e.g., quantization, distillation).
Technical skills
- Hands-on experience in fine-tuning transformer models, prompt engineering, and RAG architecture design.
- Experience delivering production-ready AI solutions in enterprise environments; telecom exposure is a plus.
- Advanced knowledge of transformer architectures, fine-tuning techniques (LoRA, PEFT, adapters), and transfer learning.
- Proficiency in Python, with significant experience using PyTorch, Hugging Face Transformers, and related NLP libraries.
- Practical expertise in prompt engineering, RAG pipelines, and LLM orchestration tools (LangChain, LlamaIndex).
- Ability to build domain-adapted LLMs, from data preparation to final model deployment.
Work Experience
7+ years of professional experience in AI/ML, with at least 2+ years of practical exposure to LLMs or GenAI deployments.
Educational Qualification
- Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, or a related field.
- Ph.D. preferred for foundational model work and advanced research focus.
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