Senior Machine Learning Engineer
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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
Requirements
- •Deep LLM Expertise: Extensive experience with transformers and advanced techniques in fine-tuning, prompt engineering, and rigorous model evaluation.
- •Senior Production Track Record: Proven history of taking complex ML projects from research 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: Drive to ship fast and iterate based on user data, maintaining a long-term technical vision.
- •Collaborative Leadership: Strong communication skills with the ability to lead remote-first teams.
Responsibilities
- •Architect and Optimize Systems: Design and oversee scalable data pipelines for model training and inference.
- •Advanced LLM Development: Lead fine-tuning, evaluation, and optimization of LLMs for Agentic Digital Assistants.
- •Production Infrastructure Leadership: Direct deployment of models on remote servers.
- •Strategic Integration: Integrate ML components into broader system architectures.
- •Model Governance: Establish monitoring frameworks and implement automated retraining loops.
- •R&D Mentorship: Stay at the forefront of AI research and tools.
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