Senior Software Engineer II

Razer Inc.; Região Norte; Presencial; BRL 487 000 - 730 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Singapore office

Resumo da oferta

Razer Inc. in Singapore seeks a seasoned AI Software Engineer to design, develop, and deploy AI-powered solutions across production systems.

You will build scalable AI pipelines, integrate ML models into applications, and collaborate with data scientists, software engineers and DevOps to bring cutting-edge AI capabilities to life. The role requires hands-on experience with Docker, Kubernetes, RESTful APIs, gRPC, and cloud platforms (AWS/Azure/GCP), plus strong Python/Java/C++ skills and a track

Qualificações

• 6+ years of AI/ML software development experience.
• Proven track record deploying AI solutions in production.

Responsabilidades

• Design, develop, and deploy AI-powered solutions.
• Build scalable AI systems and integrate ML models into applications.
• Containerize AI workloads with Docker/Kubernetes for production.
• Deploy models via RESTful APIs, gRPC, or edge solutions.
• Implement monitoring, logging, and error handling for AI systems.
• Design APIs and microservices to securely integrate AI capabilities.
• Monitor model performance and ensure SLA-compliant latency.
• Develop and maintain AI pipelines for real-time and batch processing.
• Apply MLOps practices including CI/CD for ML workflows.
• Collaborate with data scientists, software engineers and DevOps.
• Stay updated on AI/ML frameworks and industry trends.
• Identify opportunities to improve AI APIs/plugins architectures.

Conhecimentos

Python

Java

C++

TensorFlow

PyTorch

Scikit-learn

APIs

GPG/Cloud ML

Formação académica

Bachelor’s or Master’s degree in computer science/AI

Ferramentas

Docker

Kubernetes

Terraform

RESTful APIs

gRPC

Descrição da oferta de emprego

Job Responsibilities :

We are seeking skilled AI Software Engineers to design, develop, and deploy AI-powered solutions. This role involves building scalable AI systems, integrating AI / Machine Learning (ML) models into applications, and optimizing AI workflows for production. You will collaborate closely with data scientists, software engineers, and DevOps teams to bring cutting-edge AI capabilities to life.

• Implement and optimize AI / ML models in production, via containerization (Docker, Kubernetes), for speed, accuracy and cost-effectiveness
• Deploy AI models using RESTful APIs, gRPC, or edge computing solutions.
• Implement monitoring, logging, and error-handling mechanisms to track AI performance.
• Design APIs and microservices to integrate AI capabilities into software systems to ensure that they are secure, performant and well-documented
• Monitor and optimize model performance in production environments, ensuring API latency and availability meet the required SLAs (Service Level Agreements).
• Build scalable, high-performance AI pipelines for real-time and batch processing.
• Implement MLOps best practices, including CI/CD for machine learning workflows on both local machines and cloud platforms
• Work closely with data scientists to turn research models into deployable solutions.
• Collaborate with DevOps and cloud engineers to ensure seamless AI model deployment.
• Stay up to date with the latest AI/ML frameworks, tools, and industry trends in API, plugins development to continuously improve and enhance API solutions.
• Identify opportunities to improve existing AI API / plugins architectures and suggest new features or services to add value to AI products.

Pre-Requisites :

• 6+ years of experience in AI/ML software development.
• Proven track record of deploying AI solutions in production environments.
• Strong experience in deploying AI models and API development using RESTful APIs, gRPC, or edge computing solutions.
• Strong programming skills in Python, Java, or C++.
• Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• In depth understanding of containerization (Docker, Kubernetes) and DevOps practices.
• Experience in developing and deploying AI applications running both edge deployment (TensorRT, ONNX, TFLite) and on cloud infrastructure (AWS, Azure or Google Cloud Platform) using Infrastructure as code tools such as Terraform and also cloud AI services (AWS SageMaker, Google Vertex AI, Azure ML).
• Experience with database management (SQL, NoSQL, and vector databases).
• Knowledge of distributed computing (Spark, Dask) and parallel processing.
• Ability and willingness to learn any new technologies and apply them at work in order to stay ahead, in a fast paced, high pressure, agile environment
• Excellent written and verbal communication skills for coordinating across teams.

Education & Experience

• Has a Bachelor’s or Master’s degree in computer science, AI or similar discipline from an accredited institution

Travel Requirements

• Role based in Singapore office and may require up to 1 travel trip per year.