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Inferact

Member of Technical Staff, Inference

SingaporeOnsite · Singapore
Staff · FullTime · Research & Engineering
POSTED 24 JUN
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Role
138 days opentrue age
Posted 24 Jun
Payats field
SGD 200k–400kposted
● 0% vs market median SGD 300k
SGD 200kSGD 400k
Market p25–p75
SGD 300k
Inferact p25–p75
SGD 300kn=5
H-1B median · Software engineering
$360k
Singapore · n=5 · 365d to 4 Nov
CompanyInferact →
32open roles
Opened · 30d
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Closed · 30d
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3d of snapshots · 30d window
Market
9,275open · Staff Software engineering
Opened · 7d
+4855% of open
All software engineering
75,228open
All tracked boards · live 9 Nov · n=9,275
Visa
5H-1B LCAs · FY26
Median wage
$280k
LCAs FY26 · n=5 · to 2026-05-14
PythonPyTorchLLMs

Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware—a position that took years to build.

About the Role

We're looking for an inference runtime engineer to push the boundaries of what's possible in LLM and diffusion model serving. Models grow larger. Architectures shift: mixture-of-experts, multimodal, agentic. Every breakthrough demands innovations on the inference engine itself. You'll work at the core of vLLM, optimizing how models execute across diverse hardware and architectures. Your work will directly impact how the world runs AI inference.

Skills and Qualifications

Minimum qualifications:

Bachelor's degree or equivalent experience in computer science, engineering, or similar.

Deep understanding of transformer architectures and their variants.

Strong programming skills in Python with experience in PyTorch internals.

Experience with LLM inference systems (vLLM, TensorRT-LLM, SGLang, TGI).

Ability to read and implement model architectures and inference techniques from research papers.

Demonstrate the ability to contribute performant and maintainable code and debug in complex ML codebases.

Preferred qualifications:

Deep understanding of KV-cache memory management, prefix caching, and hybrid model serving.

Familiarity with RL frameworks and algorithms for LLMs.

Experience with multimodal inference (audio/image/video/text).

Contributions to open-source ML or system infrastructure projects.

Bonus points if you have:

Implemented core features in vLLM or other inference engine projects.

Contributed to vLLM integrations (verl, OpenRLHF, Unsloth, LlamaFactory, etc).

Written widely-shared technical blogs or side projects on vLLM or LLM inference.

Logistics

Location: This role is based in Singapore.

Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is S$200,000 to S$400,000 annually + equity.

Visa sponsorship: We sponsor visas on a case-by-case basis.

Benefits: Inferact offers a generous benefits package, including medical, dental, and vision coverage.

Source · InferactFirst seen 2 NovOriginal ↗