Edge AI SLM/VLM Engineer: Training & Distillation

Jabil; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Jabil in Singapore is seeking a capable engineer/researcher to lead the R&D of Small Language Models (SLMs) and Vision-Language Models (VLMs) for edge, low-latency, and cost-efficient production.

You will own continuous pretraining, supervised instruction tuning (SFT), and compression/distillation pipelines, collaborating with platform teams to achieve reliable improvements in inference efficiency and model quality.

Qualifications

• Strong software engineering skills in Python and C++ with ML training/evaluation pipelines in PyTorch.
• Hands-on experience in model efficiency and inference optimization (distillation, quantization, pruning, serving).
• Experience with high-performance computing and acceleration: CUDA and/or SIMD, profiling and performance tuning.
• Ability to read and reproduce ideas from recent papers and implement algorithms with strong experimental discipline.
• Ability to communicate effectively in English and Mandarin Chinese for cross-border liaison.

Responsibilities

• SLM/VLM Training: Continuous Pretraining & Instruction Tuning (SFT).
• Compression, Distillation & Edge/Low-Latency Inference Optimization.
• Tool Calling System: Catalog, Routing, Validation, Fallback & Observability.
• RL & Reward Modeling for Alignment and Tool-Use Reliability.
• Data Pipeline Automation (Collection, Cleaning, Curation).
• Rigorous Evaluation, Testing & Iteration.

Skills

Python

C++

PyTorch

Model optimization

CUDA

English

Mandarin Chinese

Tools

CUDA

Job description

Jabil in Singapore is seeking a capable engineer/researcher to lead the R&D of Small Language Models (SLMs) and Vision-Language Models (VLMs) for edge, low-latency, and cost-efficient production.

You will own continuous pretraining, supervised instruction tuning (SFT), and compression/distillation pipelines, collaborating with platform teams to achieve reliable improvements in inference efficiency and model quality.