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Senior Software Engineer
2 weeks ago
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.
- Bachelor's degree (or higher) in Computer Science or a related field.
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