Company Overview:
At Yurts, we are at the forefront of driving innovation in machine learning (ML) infrastructure to deliver cutting-edge solutions. Our mission is to create robust ML infrastructures leveraging Kubernetes and containerization technologies, optimizing ML inference for high-performance and low-latency models. We are seeking a highly skilled Senior Software Engineer for ML Infrastructure to join our dynamic team and lead the development of state-of-the-art ML deployment systems.
Responsibilities:
- Design, deploy, and maintain robust ML infrastructures using Kubernetes and containerization technologies to enable seamless and scalable deployment of machine learning models.
- Utilize your deep knowledge of CUDA and GPU-accelerated computing to optimize ML inference, delivering high-performance and low-latency models for demanding applications.
- Champion DevOps practices and streamline CI/CD pipelines to enhance the software development lifecycle and increase deployment efficiency.
- Lead efforts to develop and implement model scheduling and autoscaling strategies, dynamically allocating resources based on real-time inference demands to ensure optimal resource utilization.
- Collaborate with cross-functional teams, taking an active role in architectural discussions and hands-on development to drive innovation and push the boundaries of ML infrastructures.
Requirements:
- 5+ years of relevant experience in ML infrastructure development.
- 1+ years of professional development experience with Rust
- Proven track record of extensive experience with Kubernetes and containerization technologies, demonstrating a strong ability to deploy and manage distributed systems at scale.
- Hands-on experience in optimizing ML inference using CUDA and GPU-accelerated computing, achieving significant performance gains for complex ML models.
- Deep understanding of DevOps practices and experience implementing CI/CD pipelines, ensuring a smooth and efficient development and deployment process.
- Demonstrated expertise in model scheduling and autoscaling techniques, allowing dynamic resource allocation to meet varying inference workloads.
- Strong architectural and software development skills, with a passion for crafting elegant and efficient solutions that push the boundaries of ML infrastructure capabilities.
Preferred Qualifications (not mandatory):
- Experience in deploying and managing machine learning models in cloud environments such as AWS, GCP, or Azure.
- Knowledge of machine learning frameworks such as TensorFlow, PyTorch, or ONNX, and their integration with inference engines
Note:
At Yurts, we believe in harnessing the power of ML infrastructure to achieve outstanding performance. If you're interested in exploring the possibilities of machine learning and its potential impact, check out our blog: The bridge to enterprise AI | Yurts Enterprise AI | Blog for fascinating insights. This will give you a glimpse of the exciting world of ML infrastructure and its applications.Compensation Information$200,000 - $250,000USD
