Ai/Ml Engineer

Hcltech

Milano

In loco

EUR 70.000 - 110.000

Tempo pieno

2 giorni fa
Candidati tra i primi
Generatore di candidature

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Descrizione del lavoro

HCLTech in Milan, Italy, is seeking a Mid to Senior AI/ML Engineer to join a multidisciplinary team building production-grade AI solutions centered on Large Language Models (LLMs). You will develop and fine-tune LLMs, design RAG pipelines, and deploy AI components for fraud prevention in the telecom sector.

You will collaborate with engineers and data scientists to optimize models, manage datasets and experiments, and contribute to scalable, high-impact AI systems in an agile environment.

Competenze

  • Bachelor's or Master's degree in Computer Science or related field.
  • Strong English communication skills.
  • Team-oriented and collaborative mindset.

Mansioni

  • Develop and deploy AI/ML solutions using Python.
  • Design and implement LLM-based systems, including fine-tuning approaches (LoRA, PEFT).
  • Build and optimize RAG pipelines and vector-based retrieval systems.
  • Collaborate on model evaluation, experimentation, and performance optimization.
  • Manage datasets, experiment tracking, and evaluation pipelines.
  • Contribute to scalable deployment and integration of AI components.
  • Work closely with cross-functional teams in an agile environment.

Conoscenze

Machine Learning
LLM fine-tuning
RAG retrieval
ML frameworks
Experiment tracking
English communication

Formazione

Bachelor's or Master's in Computer Science

Strumenti

PyTorch
TensorFlow
Transformers
LangChain
Cloud platforms
Docker/Kubernetes

Descrizione del lavoro

We are seeking a Mid to Senior AI/ML Engineer to join a multidisciplinary team focused on building production-grade AI solutions centered on Large Language Models (LLMs). This role involves hands-on development of LLM fine-tuning and Retrieval-Augmented Generation (RAG) architectures, contributing to scalable and high-impact AI systems.

You will collaborate closely with engineers and data scientists to design, optimize, and deploy AI models, primarily supporting fraud prevention solutions within the telecommunications domain. The position offers increasing ownership of technical and architectural decisions.

Key Responsibilities
  • Develop and deploy AI/ML solutions using Python
  • Design and implement LLM-based systems, including fine-tuning approaches (LoRA, PEFT)
  • Build and optimize RAG pipelines and vector-based retrieval systems
  • Collaborate on model evaluation, experimentation, and performance optimization
  • Manage datasets, experiment tracking, and evaluation pipelines
  • Contribute to scalable deployment and integration of AI components
  • Work closely with cross-functional teams in an agile environment
Primary Skill
Secondary Skills
  • Solid foundations in Machine Learning and AI
  • Experience with LLMs and fine-tuning techniques (LoRA, PEFT)
  • Hands-on experience with RAG and vector-based retrieval
  • Experience with AI/ML frameworks such as PyTorch, TensorFlow, Transformers, and LangChain
  • Ability to manage datasets, experiments, and evaluation workflows
Additional / Preferred Skills
  • Advanced experience in LLM optimization or adaptation
  • Exposure to MLOps / AIOps (deployment, monitoring, lifecycle management)
  • Experience with cloud platforms or containerized environments
  • Knowledge of graph analytics
  • Background in fraud detection, anomaly detection, or complex data analytics
Qualifications
  • Bachelor’s or Master’s degree in Computer Science or a related technical field
  • Strong communication skills in English
  • Team-oriented mindset with the ability to work in collaborative environments
About HCLTech

HCLTech is a global technology company with over 226,000 employees across 60 countries. We deliver industry-leading capabilities in AI, digital, engineering, cloud, and software services. Our expertise spans multiple industries including Financial Services, Manufacturing, Healthcare, Telecom, and Semiconductor, helping clients drive innovation and transformation at scale.

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