Senior AI Software Engineer - AI Integration

1 Month ago • 3 Years + • Research Development

Job Summary

Job Description

The Senior AI Software Engineer will design, develop, and deploy AI-powered solutions, integrating AI/ML models into applications and optimizing workflows for production. Responsibilities include implementing and optimizing AI models, deploying models using APIs, and implementing monitoring and logging. They will design APIs and microservices, monitor model performance, build scalable pipelines, implement MLOps practices, and collaborate with data scientists and DevOps teams. The role requires staying updated on AI/ML trends and improving AI architectures. This role involves working in a fast-paced, agile environment and requires excellent communication skills to coordinate across teams. The candidate should have experience deploying AI solutions and building AI pipelines.
Must have:
  • 3+ years of AI/ML software development experience
  • Experience deploying AI solutions in production
  • Strong programming skills in Python, Java, or C++
  • Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn)
  • Experience in containerization (Docker, Kubernetes)
  • Experience in deploying AI applications on cloud infrastructure
  • Experience with database management (SQL, NoSQL, and vector databases)

Job Details

Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.

Job Responsibilities :

We are seeking a highly skilled AI Software Engineer 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 :

  • 3+ 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

Are you game?

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About The Company

At Razer, you'll be at the forefront of the most exciting industry in the world — gaming. Evolving forms of gaming require evolving forms of hardware, software and services. That’s where Razer comes in, offering innovative top-of-the-line products and services to allow gamers to fully immerse in the ultimate gaming experience.Getting onboard Razer will place you on a global mission to bring gamers closer to the games they love. Razer is a place to do great work, offering you the opportunity to be a part of a global team across 11 countries. Whether you are a hardcore evangelist who breathe life to the latest and greatest gaming gear or a behind-the-scene hero who runs our global operations, you are assured of a career-changing quest that transcends time zones and culture with one single spell: For Gamers. By Gamers.The journey towards phenomenal-ness won’t come easy. However, we will excel because gamers rely on teamwork. We achieve greatness because we are wicked problem-solvers and tenacious in clinching victories in all that we do. It is the team that makes Razer where it is today and will continue to bring Razer to even greater heights.

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