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GenAI/LLM Engineer – Domain-Specific AI Solutions
4 weeks ago
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. Know our story: in Silicon Valley, Mobileum has global offices in Australia, Dubai, Germany, Greece, India, Portugal, Singapore and UK with global HC of 1800+.
Join Mobileum Team
At Mobileum we recognize that our team is the main reason for our success. What does work with us mean? Opportunities
Role Overview:
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.
Key Responsibilities:
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.
Required Skills:
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.
Desirable Bonus Skills:
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).
Experience:
6–8 years of professional experience in AI/ML , with at least 2+ years of practical exposure to LLMs or GenAI deployments .
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.
Qualifications:
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.
What We Offer:
Opportunity to lead cutting-edge GenAI initiatives in the telecom sector.
High ownership of end-to-end productization lifecycle of domain-specific LLMs .
Collaborative environment with AI, telecom, and product leaders .
Competitive compensation with options for rapid career growth in an enterprise AI transformation journey.
