9 дней назад
Software Engineer, ML Infrastructure, Content Retrieval Platform, Level 4 (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Software Engineer, ML Infrastructure, Content Retrieval Platform, Level 4 (AI): Building large-scale retrieval, feature generation, model serving, and ML training infrastructure with an accent on distributed systems, high-performance inference, and production reliability. Focus on designing scalable cloud systems, optimizing AI model serving, and developing data pipelines for online inference and offline training.
Location: Palo Alto, United States; office work expected 4+ days per week under Snap's “default together” policy
Company
Snap develops and other digital services focused on visual communication, augmented experiences, and social products.
What you will do
- Design and optimize large-scale ML infrastructure systems, improving reliability, performance, and efficiency.
- Build feature generation and serving pipelines for online inference and offline training data.
- Develop high-performance inference and model-serving systems.
- Build cloud infrastructure for scalable ML training, evaluation, and inference.
- Develop data management systems for collection, labeling, processing, and evaluation.
- Collaborate with ML engineers to deploy models into production using secure, production-ready engineering practices.
Requirements
- Bachelor’s degree in computer science or a related technical field, or equivalent experience.
- At least 2 years of post-bachelor’s software development experience, or equivalent experience with a master’s or PhD.
- Experience building large-scale production ML systems, distributed systems, or big data processing systems.
- Strong programming skills in Python and Java.
- Knowledge of distributed systems, large-scale ML infrastructure, and system performance optimization.
- Experience with Spark, Flink, Ray, or similar big data processing frameworks.
Nice to have
- Master’s or PhD in a technical field or equivalent industry experience.
- Experience with ML training platforms or AI model inference optimization.
- Familiarity with TensorFlow, PyTorch, Caffe2, Spark ML, scikit-learn, or related frameworks.
Culture & Benefits
- In-person collaboration through the “default together” office policy.
- Paid parental leave and comprehensive medical coverage.
- Emotional and mental health support programs.
- Compensation packages connected to Snap’s long-term success.
- Equal opportunity employment and workplace accommodation support.
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