Mid-Senior GenAI / Machine Learning Engineer (Telecom Domain)

We're looking for a Mid-Senior GenAI/Machine Learning Engineer with hands-on AI/ML experience and a strong background in telecommunications. You'll design and deploy Generative AI applications, work with Large Language Models (LLMs), and build ML solutions addressing real telecom use cases — customer support, network optimization, operations, and predictive analytics. What You'll Do • Design, develop, and deploy Generative AI and Machine Learning solutions for telecom business use cases • Build AI-powered applications using LLMs, Retrieval-Augmented Generation (RAG), and AI agents • Develop scalable ML pipelines for model training, evaluation, deployment, and monitoring • Partner with business stakeholders, data engineers, and solution architects to translate requirements into AI solutions • Fine-tune foundation models and optimize prompt engineering strategies • Work with structured and unstructured telecom data to build predictive and conversational AI solutions • Integrate AI/ML models with cloud platforms and enterprise applications • Ensure AI solutions follow security, governance, and responsible AI best practices What You Bring • 5–8 years of experience in Machine Learning, Data Science, or Artificial Intelligence • 2+ years of hands-on experience with Generative AI technologies • Strong Python skills and experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn) • Experience working with LLMs (OpenAI, Llama, Claude, Gemini, etc.) • Hands-on experience with RAG architectures, vector databases (Pinecone, FAISS, Chroma, or Milvus), and prompt engineering • Experience with AI orchestration frameworks such as LangChain or LlamaIndex • Solid understanding of NLP, embeddings, model evaluation, and AI application development • Experience with Azure AI, Azure OpenAI, AWS Bedrock, or Google Vertex AI • Working knowledge of REST APIs, Docker, Git, and CI/CD pipelines • Telecom domain experience required Important • Candidates must be local to Dallas, TX or willing to be onsite 3 days/week • Final round interview is mandatory onsite — candidates unable to attend in person will not be considered Interested candidates should apply directly or reach out for more details.