Principal Machine Learning Engineer
Extreme Networks- Location
- Global
- Workplace
- Remote
- Employment
- Full Time
- Salary
- —
Posted 1mo ago
The employer’s full description could not be read from their board. This is a summary of the posting — follow the apply link for the original.
Responsibilities
- Drive an innovative vision for products and platforms
- Design and launch strategic machine learning (ML) solutions
- Drive business-wide innovation
- Lead the end-to-end software development lifecycle
- Lead technical discussions and strategy
- Participate hands-on in design reviews, code reviews, and implementation
- Craft high-performance, production-ready machine learning code
- Extend existing ML libraries and frameworks
- Lead solutions to accelerate model development, validation and experimentation cycles
- Integrate models and algorithms in production systems at a very large scale
- Mentor and develop other engineers on the team
- Establish technical direction
- Foster team culture
- Uphold the highest standards of technical rigor
- Build highly resilient and scalable systems
- Champion operational and process improvements
Requirements
- Degree in mathematics/computer science or related discipline
- 12+ years of experience in the complete software development lifecycle
- 7+ years of experience in programming, with proficiency in at least one programming language, preferably Python or Java
- 5+ years of experience in leading the design and architecture of large distributed systems preferably on cloud platforms (e.g., AWS, Azure, Google Cloud)
- Experience working with distributed data and ML technologies (e.g. MapReduce, Spark, Flink, Kafka, PySpark, SageMaker etc.)
- Experience as a mentor, tech lead or leading an engineering team
- Adept at tackling highly complex, ambiguous or undefined problems
Preferred
- MS or PhD in Computer Science or equivalent experience in ML
- Experience dealing with real world large-scale datasets
- Prior experience delivering end-to-end ML solutions, including data preparation, training, fine-tuning and deployment of large models
- Prior experience in developing ML optimization techniques in frameworks like PyTorch and CUDA
Skills
- Python
- Java
- Cloud
- PyTorch
- CUDA
- MapReduce
- Spark
- Flink
- Kafka
- PySpark
- SageMaker
- AWS
- Azure
- Google Cloud
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