About Us :
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.
Solution Engineer • Delhi, India