LLM Post-Training & Evaluation Engineer

Nezda Global; Philippines; On-site; PHP 600,000 - 1,200,000; Full time

Job summary

Nezda Global seeks an AI/ML Research Engineer – LLM Post-Training & Evaluation to design and implement pipelines that connect data, evaluation, and model post-training. You will advance SFT, DPO, RLHF/RLAIF workflows, automated evaluation, and multimodal model assessment.

This hands-on role bridges research and production ML engineering, mentoring engineers and collaborating with data scientists and customer stakeholders to deliver robust evaluation frameworks and reusable ML infrastructure.

Qualifications

• 2–3+ years of ML engineering, applied ML systems, or research engineering experience.
• BS/MS/PhD in Computer Science, Machine Learning, AI, Applied Mathematics, or related quantitative field.
• Hands-on experience with LLM training, fine-tuning, or post-training.
• Experience with SFT, DPO, or foundation model/domain adaptation.
• Strong Python programming and software engineering fundamentals.
• Experience with PyTorch, JAX, or TensorFlow.

Responsibilities

• Lead or co-lead technically complex ML engineering projects from discussion through delivery.
• Build and optimize LLM training and post-training pipelines.
• Develop data ingestion, preprocessing, fine-tuning, evaluation, and experiment-tracking workflows.
• Build automated evaluation pipelines, benchmarks, and task-specific test harnesses.
• Integrate human and AI-augmented evaluation signals into model development.
• Improve reproducibility, metrics logging, regression monitoring, and experiment reliability.
• Diagnose model behavior, training issues, data problems, and evaluation inconsistencies.
• Work with Language Data Scientists and Applied Research Scientists to implement evaluation frameworks.
• Collaborate directly with customer technical stakeholders.
• Contribute to internal R&D, benchmark frameworks, evaluation tooling, and reusable ML infrastructure.
• Mentor junior engineers and contribute to technical design reviews and engineering standards.

Skills

Python programming

ML engineering fundamentals

Distributed ML systems

Collaboration with researchers

Research-to-production bridge

Education

BS/MS/PhD in CS/ML/Applied Math

Tools

Hugging Face ecosystem

PyTorch

JAX

TensorFlow

vLLM

distributed training stacks

Job description

Nezda Global seeks an AI/ML Research Engineer – LLM Post-Training & Evaluation to design and implement pipelines that connect data, evaluation, and model post-training. You will advance SFT, DPO, RLHF/RLAIF workflows, automated evaluation, and multimodal model assessment.

This hands-on role bridges research and production ML engineering, mentoring engineers and collaborating with data scientists and customer stakeholders to deliver robust evaluation frameworks and reusable ML infrastructure.