Job Opportunity: Senior Python Developer (AIML)
Location:
Singapore, Singapore
Experience:
5-10 years
Employment Type:
Full-time, Morning Shift, Onsite
NOTE: Only Singaporean locals or PR holders can apply.
About the Role
We are seeking an experienced
Machine Learning Engineer
with deep expertise in
Python
,
AI/ML frameworks
, and
cloud-native infrastructure
. You will play a key role in designing, developing, and deploying scalable machine learning solutions—covering the entire AI/ML lifecycle from model development to deployment, serving, and monitoring in production environments.
Key Responsibilities
Design, develop, and deploy
AI/ML solutions
using modern frameworks and infrastructure.
Write clean, efficient, and scalable
Python code
for machine learning, data processing, and automation workflows.
Work across
cloud infrastructure components
—including compute, networking, and storage—with a focus on
Kubernetes-based environments
.
Build, implement, and maintain
MLOps pipelines
encompassing model training, deployment, serving, and monitoring.
Optimize and manage
Large Language Model (LLM)
inference and performance using frameworks such as
vLLM
,
SGLang
, or
TensorRT-LLM
.
Integrate and support
model serving and orchestration frameworks
including
MLflow
,
Seldon
,
Triton Inference Server
, or
Ray Serve
.
Collaborate closely with
data scientists
,
software engineers
, and
DevOps teams
to ensure reliable, scalable, and efficient AI/ML operations.
Required Qualifications
Bachelor’s or Master’s degree in
Computer Science
,
Artificial Intelligence
,
Data Engineering
, or a related field.
Proven proficiency in
Python
, with experience developing
production-grade AI/ML applications
.
Strong understanding of
machine learning concepts
, algorithms, and model development workflows.
Hands-on experience with
cloud infrastructure
and
container orchestration
(especially
Kubernetes
).
Familiarity with the
AI/ML lifecycle
and
MLOps practices
, including model deployment, serving, and monitoring.
Preferred Qualifications
Experience with
LLM inference frameworks
(e.g.,
vLLM
,
SGLang
,
TensorRT-LLM
).
Familiarity with
model serving/orchestration frameworks
such as
MLflow
,
Seldon
,
Triton Inference Server
, or
Ray Serve
.
Understanding of
model optimization
,
scaling
, and
performance tuning
for LLMs and deep learning workloads.
Experience in
cloud-native AI/ML environments
(e.g.,
GCP
,
AWS
, or
Azure
).
Does this sound like you or someone you know? Kindly send your CV here: gealyn.pafin@prideglobal.com
Looking forward to meeting you!