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 solutionscovering 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 componentsincluding compute, networking, and storagewith 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: [Confidential Information]
Looking forward to meeting you!
