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Machine Learning Engineer, Foundation Models
Job Description
Meta AI is dedicated to advancing the field of artificial intelligence. We are looking for experienced Machine Learning Engineers to join our Foundation Models team. You will be instrumental in building, scaling, and optimizing large-scale AI models that power a wide range of Meta products and research initiatives. This role involves working on the entire ML lifecycle, from data processing and model training to deployment and performance monitoring. You'll tackle complex engineering challenges related to distributed training, efficient inference, and robust model evaluation.
**Responsibilities:**
* Design, build, and deploy large-scale machine learning models.
* Optimize model training and inference for performance and efficiency.
* Develop and maintain ML infrastructure and tooling.
* Collaborate with research scientists to bring state-of-the-art models into production.
* Ensure the reliability, scalability, and maintainability of ML systems.
**Minimum Qualifications:**
* BS/MS degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
* 3+ years of experience in machine learning engineering.
* Strong programming skills in Python and C++.
* Experience with ML frameworks like PyTorch or TensorFlow.
* Experience with distributed systems and large-scale data processing.
**Preferred Qualifications:**
* Experience with foundation models (LLMs, diffusion models, etc.).
* Familiarity with cloud platforms (AWS, GCP, Azure).
* Experience with MLOps practices.
Skills & Tags
ml engineeringfoundation modelsllmpytorchdistributed systems