Technical Lead

Job Summary

CTG Tracking ID-RDRI15

HM Name-52292013 Costanzo

"We are looking for a mid to senior AI/ML engineer to join a multidisciplinary team building production grade AI solutions centered on Large Language Models (LLMs).
The role involves hands on work on LLM fine tuning and Retrieval Augmented Generation (RAG) architectures, contributing to design, implementation, and integration of scalable AI components. You will collaborate closely with engineers and data scientists on model evaluation, optimization, and deployment.
The main application area is fraud prevention in the telecommunications sector. The role offers growing autonomy in technical and architectural decisions.
A degree in Computer Science or a related technical field is required."

Key Responsibilities

1. To be responsible for providing technical guidance / solutions ;define, advocate, and implement best practices and coding standards for the team.

2. To develop and guide the team members in enhancing their technical capabilities and increasing productivity

3. To ensure process compliance in the assigned module| and participate in technical discussions/review as a technical consultant for feasibility study (technical alternatives, best packages, supporting architecture best practices, technical risks, breakdown into components, estimations).

4. To prepare and submit status reports for minimizing exposure and risks on the project or closure of escalations.

Skill Requirements

"• Strong Python skills for AI/ML development

• Solid foundations in Machine Learning and AI
• Proven experience with LLMs and fine tuning techniques (e.g. LoRA, PEFT)
• Hands on experience with RAG and vector based retrieval
• Experience with AI/ML frameworks (Py Torch, Tensor Flow, Transformers, Lang Chain)
• Ability to manage datasets, experiments, and evaluation pipelines
• Strong technical English and team oriented mindset"

"• Advanced LLM adaptation or optimization experience

• Exposure to MLOps / AIOps (deployment, monitoring, lifecycle management)
• Experience with cloud or containerized environments
• Knowledge of graph analytics
• Background in fraud detection, anomaly detection, or complex data analytics"

Other Requirements

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