Intracom Telecom

Senior ML Engineer

Intracom Telecom

full-time

Posted on:

Location Type: Hybrid

Location: Paiania • Greece

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Job Level

Senior

Tech Stack

CloudDjangoDockerGrafanaJavaJenkinsKerasKubernetesLinuxPrometheusPythonPyTorchScikit-LearnTensorflow

About the role

  • **Key Responsibilities:**
  • - Design, implement, and maintain production-grade AI systems, including traditional ML and LLM-based agentic solutions
  • - Own end-to-end ML and LLM pipelines, from data processing and feature pipelines to deployment, monitoring, and continuous improvement
  • - Build and operate efficient LLM inference and serving stacks, including deployment and optimization (e.g., batching, quantization, scalable runtimes, vLLM)
  • - Lead architectural and technical decisions, setting best practices, coding standards and mentoring engineers
  • - Collaborate closely with product managers, software engineers, and stakeholders to translate business needs into scalable AI solutions
  • - Ensure reliability, scalability, and observability of AI in production
  • - Contribute to and evolve the team’s MLOps processes, including CI/CD, automation, and model lifecycle management

Requirements

  • - BSc in Computer Science, Electrical and Computer Engineering, or related field
  • - Proven experience delivering production AI systems as an ML / Software Engineer
  • - Strong understanding of machine learning and applied AI in production environments
  • - Hands-on experience with end-to-end ML and LLM pipelines and LLM-based systems (conversational AI, RAG, agentic workflows, vector databases)
  • - Experience deploying and optimizing LLMs in production, including inference tuning and efficient serving
  • - Solid experience with MLOps practices (CI/CD, model versioning, lifecycle management)
  • - Excellent proficiency in Python, plus experience in at least one additional production language (e.g., Java or C++)
  • - Experience designing scalable AI architectures and integrating them into existing products and platforms
  • - Experience with ML/AI frameworks (PyTorch, TensorFlow/Keras, Scikit-learn) and LLM orchestration tools (LangChain, LangGraph, etc.)
  • - Familiarity with containerized deployments (Docker, Kubernetes) and cloud platforms
  • - Strong problem-solving skills and fluency in English
  • - Familiarity with S/W development practices and verification frameworks (git, Gitlab, GitHub, CircleCI, Sonar, Jenkins, etc.)
  • **Nice to have**
  • - Data engineering or large-scale data pipeline experience
  • - Knowledge of telecommunication networks and networking protocols
  • - Exposure to 5G RAN architecture is highly appreciated
  • - Experience working in regulated environments or with enterprise-grade systems
  • - Backend development (e.g., Django) and strong Linux networking knowledge
  • - Familiarity with observability tools (Prometheus, Grafana, ELK/OpenSearch)
Benefits
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Applicant Tracking System Keywords

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Hard Skills & Tools
machine learningapplied AIend-to-end ML pipelinesLLM-based systemsMLOps practicesPythonJavaC++ML/AI frameworkscontainerized deployments
Soft Skills
problem-solvingmentoringcollaborationcommunicationleadership
Certifications
BSc in Computer ScienceBSc in Electrical and Computer Engineering