Senior Software Engineer

2 weeks ago


Bengaluru, Karnataka, India Zyoin group Full time


We are seeking a highly experienced Senior Software Engineer with expertise in Machine Learning (ML) Infrastructure to join our team.


  • The ideal candidate will have a strong background in designing largescale and production ML infrastructure systems or distributed systems.
  • This role requires deep knowledge of building distributed systems or recommendation infrastructure, proficiency in at least one programming language (Java, C++, Python), and a good understanding of system architecture.
  • The Senior Software Engineer will contribute to the design and development of ML infrastructure, big data technologies, streaming architecture, data pipelines, and more.
  • Experience with Kubernetes, ML offerings from AWS and GCP, and ML model serving complexities are preferred.
  • A BS degree (or higher) in Computer Science or a related field is required.

Key Responsibilities:

Design and Develop ML Infrastructure:

  • Design, architect, and develop largescale ML infrastructure systems for production environments.
  • Contribute to the development of distributed systems or recommendation infrastructure.

System Architecture:

  • Apply a deep understanding of system architecture principles to design robust and scalable ML infrastructure solutions.
  • Collaborate with crossfunctional teams to ensure alignment with overall system architecture goals.

Big Data Technologies and Streaming Architecture:

  • Leverage expertise in big data technologies and streaming architecture to build efficient data pipelines and processing systems.
  • Optimize data ingestion, storage, and processing mechanisms for performance and scalability.

Cloud Platform Experience:

  • Work with Kubernetes for container orchestration and deployment.
  • Utilize ML offerings from AWS and GCP to leverage cloudbased ML capabilities.

ML Model Serving:

  • Handle complexities of ML model serving using frameworks such as TorchServe, TensorFlow Serving, NVIDIA Triton Inference Server, etc.
  • Optimize model serving performance and efficiency through hardware accelerator libraries like Cuda and Quantization.

Research and Development:

  • Stay updated with the latest advancements in ML infrastructure technologies and contribute to research and development efforts within the team.

Required Skills and Qualifications:

  • 5+ years of relevant industry experience in designing largescale and production ML infrastructure systems or distributed systems.
  • Deep knowledge of building distributed systems or recommendation infrastructure.
  • Proficiency in at least one programming language: Java, C++, Python.
  • Strong understanding of system architecture principles.
  • Experience with big data technologies, streaming architecture, and data pipelines.
  • Working experience with Kubernetes and ML offerings from AWS and GCP is preferred.
Experience in complexities of ML model serving and hands-on experience with model/hardware accelerator libraries is preferred.

  • Bachelor's degree (or higher) in Computer Science or a related field.
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