Machine Learning Engineer - Model Training Infrastructure
4 Months ago • 5 Years + • $334,000 PA - $435,000 PA
Devops
Job Description
The Machine Learning Engineer will be responsible for designing and implementing a global-scale machine learning system for feeds, ads, and search ranking models. The role involves improving the usability and flexibility of the machine learning infrastructure, enhancing model training and serving workflows, data pipelines, storage systems, and resource management for multi-tenancy machine learning systems. The engineer will also design and develop key components of ML infrastructure, mentor interns, and contribute to the overall advancement of the company's AI infrastructure and recommendation platform. This role demands a strong understanding of large-scale system development and experience with deep learning frameworks and core machine learning infrastructure.
Good To Have:
- Experience contributing to an open-sourced machine learning framework (TensorFlow/PyTorch).
- Experience in using/designing open-source machine learning lifecycle management systems: TFX
Must Have:
- 5+ years of experience in developing and deploying large-scale systems.
- Proficiency in C/C++/CUDA/Python and solid programming skills.
- Familiarity with deep learning frameworks (TensorFlow/Pytorch).
Perks:
- Day one access to medical, dental, and vision insurance.
- 401(k) savings plan with company match.
- Paid parental leave.
- Short-term and long-term disability coverage.
- Life insurance.
- Wellbeing benefits.
- 10 paid holidays per year.
- 10 paid sick days per year.
- 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).
The mission of our AML team is to push the next-generation AI infrastructure and recommendation platform for the ads ranking, search ranking, live & ecom ranking in our company. We also drive substantial impact on core businesses of the company. Currently, we are looking for Machine Learning Engineer in Model Training Infrastructure to join our team to support and advance that mission. Responsibilities: - Responsible for the design and implementation of a global-scale machine learning system for feeds, ads and search ranking models. - Responsible for improving use-ability and flexibility of the machine learning infrastructure. - Responsible for improving the workflow of model training and serving, data pipelines, storage system and resource management for multi-tenancy machine learning systems. - Responsible for designing and developing key components of ML infrastructure and mentoring interns.
Qualifications
Minimum Qualifications - At least 5 years of experience in developing and deploying large-scale systems. - Proficient in C/C++/CUDA/Python, and have solid programming skills. - Familiar with deep learning frameworks (TensorFlow/Pytorch). - Experience on improving core machine learning infrastructure(TensorFlow, Pytorch, and Jax). Preferred Qualifications: - Experience contributing to an open sourced machine learning framework (TensorFlow/PyTorch). - Experience in using/designing open-source machine learning lifecycle management systems: TFX
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