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Jobs in Singapore   »   Jobs in Singapore   »   Engineering Job   »   Large Language Models (LLM) Engineer
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Large Language Models (LLM) Engineer

Rhipe Singapore Pte. Ltd.

Rhipe Singapore Pte. Ltd. company logo

We are seeking a well qualified candidate to join us as Large Language Models (LLM) Engineer.

The primary responsibility of this role is to develop, deploy and optimize Large Language Models and machine learning solutions into production either on-premises or on cloud platforms.


Roles & Responsibilities:

· Work closely with clients to understand their requirements and deliver custom solutions.

· Extend prototypes and improve them to robust and scalable solutions.

· Design and fine-tune large language models for specific applications.

· Efficiently handle large language models in production environments to enable (almost) real-time solutions.

· Build and run ML pipelines, and deploy models that improve accuracy of various process steps within our pipeline.

· Write technical papers, reports, and document best practices.


Important Personal Traits:

· Learning oriented and keen on stay updated on cutting-edge advancements in large language models and NLP.

· Strong analytical and problem-solving skills.

· Excellent communication skills.


Job Requirements:

· 3+ years of experience in NLP or a similar role.

· Understanding of data structures, data modeling, ML algorithms and software architecture.

· Experience writing code in Python+ ML frameworks (like Keras or PyTorch) and libraries (like scikit-learn).

· Practical experience with ML cloud Services on AZure or AWS (I.e. Azure ML,Amazon SageMaker or MLFlow)

· Basic understanding of access management, e.g. IAM and RBAC

· Optimization experience in areas such as deep learning computational frameworks is a plus

· Masters or PHD degree in a relevant field (Computer Sciences, Information Technology, Mathematics, Physics, etc.)


Good to have:

· Experience with CI/CD systems (Jenkins, Azure DevOps or similar).

· Solid understanding and practical experience with Git, Linux, Containers and Kubernetes.

· Basic understanding of infrastructure aspects including networking and storage.

· Familiarity with GPU hardware architecture, proficiency in CUDA, etc.,

· Cloud Certifications – ML Speciality.

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