Senior Machine Learning Engineer

Phaze; Muscat; On-site; OMR 23,070 - 30,760; Full time

Job summary

Phaze in Muscat is seeking a Senior Machine Learning Engineer to lead the development and scaling of sophisticated AI products. The ideal candidate will architect data pipelines, optimize LLMs for production, and oversee deployment on cloud platforms. A strong background in Python, deep learning, and MLOps is essential, alongside proven leadership in managing complex ML projects. Join us to drive innovation in AI while mentoring a dynamic team in a collaborative environment.

Qualifications

• Extensive experience with transformers and advanced techniques in fine-tuning, prompt engineering, and rigorous model evaluation.
• Proven history of taking complex ML projects from research notebooks to successful, large-scale production environments.
• Mastery of Python and deep learning.

Responsibilities

• Design and oversee the development of scalable data pipelines for complex model training and real-time inference.
• Lead the fine-tuning, evaluation, and optimization of Large Language Models (LLMs) for production-level agents.
• Direct the deployment of models on remote servers, ensuring high performance and cost-efficiency.
• Work closely with cross-functional teams to integrate ML components into system architectures.
• Establish monitoring frameworks to track model performance.
• Stay at the forefront of AI research and translate new techniques into actionable strategies.

Skills

Deep LLM Expertise

Senior Production Track Record

Expert Programming & Framework Knowledge

MLOps Mastery

Strategic Builder Mentality

Collaborative Leadership

Tools

Python

MLflow

Weights & Biases

Docker

AWS

GCP

OCI

Job description

The Role

PhazeRo is looking for a Senior Machine Learning Engineer who will take a technical leadership role in architecting and scaling real-world AI products. You will be responsible for contributing to and overseeing the end-to-end lifecycle of high-impact agentic systems, moving beyond individual experimentation to leading the deployment of robust, production-grade models. You will serve as a technical mentor for the team, driving best practices in Software Engineering, MLOps, and LLM optimization to power next-generation user experiences.

Core responsibilities

• Architect and Optimize Systems: Design and oversee the development of scalable data pipelines for complex model training and real-time inference.
• Advanced LLM Development: Lead the fine-tuning, evaluation, and optimization of Large Language Models (LLMs) specifically for production-level Agentic Digital Assistants.
• Production & Infrastructure Leadership: Direct the deployment of open-source and proprietary models on remote servers, ensuring high performance, low latency, and cost-efficiency.
• Strategic Integration: Work closely with cross-functional engineering leads to integrate sophisticated ML components into broader system architectures.
• Model Governance: Establish robust monitoring frameworks to track model performance and implement automated retraining loops to maintain quality and relevance.
• R&D Mentorship: Stay at the forefront of AI research and tools, translating new techniques into actionable strategies for the team.

What we value

• Deep LLM Expertise: Extensive experience with transformers and advanced techniques in fine-tuning, prompt engineering, and rigorous model evaluation.
• Senior Production Track Record: A proven history of taking complex ML projects from research notebooks to successful, large-scale production environments.
• Expert Programming & Framework Knowledge: Mastery of Python and deep learning.
• MLOps Mastery: Deep familiarity with professional MLOps tooling (e.g., MLflow, Weights & Biases, Docker) and cloud-native architectures on OCI, AWS or GCP.
• Strategic Builder Mentality: A drive to ship fast and iterate based on user data, while maintaining a long-term technical vision for product growth.
• Collaborative Leadership: Strong communication skills with the ability to lead remote-first teams and foster a culture of technical excellence and inclusion.