Machine Learning Research Intern at Bell Labs collaborating with scientists on innovative machine learning research and thesis projects in AI and telecommunications.
EN
Hybrid Senior Machine Learning Engineer – Gen AI, Machine Learning, Graph ML
Posted last week
About the role
- AI Staff Machine Learning Engineer at Extreme Networks developing innovative AI platforms and solutions for cloud-based networking. Join a leader in digital transformation efforts and machine learning.
Responsibilities
- Be a thought leader and forward thinker, help drive an innovative vision for our various products and platforms, design and launch strategic machine learning (ML) solutions and drive business-wide innovation.
- Take the lead in the end-to-end software development lifecycle, encompassing design, testing, deployment, and operations, lead technical discussions and strategy, and participate hands-on in design reviews, code reviews, and implementation.
- Craft high-performance, high-scale microservices architectures, including synchronous and asynchronous web services.
- Develop real-time online inferencing for highly complex models using Triton, TensorRT and mixed precision computing.
- Mentor and develop other engineers on the team, establish technical direction and foster team culture.
- Uphold the highest standards of technical rigor in engineering and operational excellence, build highly resilient and scalable systems, and champion operational and process improvements.
Requirements
- Degree in mathematics/computer science or related discipline.
- 5 to 10 years of experience in the complete software development lifecycle including design, coding, code reviews, testing, build processes, deployments and operations.
- 5 to 10 years of experience in Python with an in-depth knowledge of its advanced features and libraries.
- Expertise in designing RESTful APIs with hands-on experience with technologies such as FastAPI.
- Proficient in Docker, Kubernetes, and modern CI/CD practices.
- 3+ years of experience in leading the design and architecture of large distributed systems preferably on cloud platforms (e.g., AWS, Azure, Google Cloud).
- Experience as a mentor, tech lead or leading an engineering team.
Benefits
- Benefits based on qualifications, experience and region.
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