1 day ago
Base Salary
$154k - $217k/yr
Responsibilities
- Design, develop, and deploy large-scale machine learning models and AI pipelines for ranking, recommendation, and generative AI systems.
- Own end-to-end technical design decisions for AI/ML systems, including modeling approaches, training strategies, and inference frameworks.
- Profile and optimize ML training and serving pipelines to reduce latency and improve compute efficiency.
- Build model evaluation, monitoring, online experimentation, staged rollout, and regression-detection processes.
- Collaborate with product managers, data scientists, and research scientists to translate product needs into ML solutions and measurable product improvements.
- Build reusable AI tooling and infrastructure components and improve developer workflows for model development and deployment.
- Apply privacy-by-design principles and integrity safeguards while meeting data governance and compliance requirements.
- Mentor engineers and contribute to recruiting and technical community programs.
- Lead incident retrospectives and help improve operational readiness for production ML systems.
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
- 6+ years of experience designing, training, and deploying machine learning or deep learning models in production.
- 6+ years of experience with ML frameworks such as PyTorch or TensorFlow and proficiency in Python.
- Experience with large-scale distributed training, model optimization techniques such as quantization, distillation, and pruning, and ML serving infrastructure.
- Experience designing and running online A/B experiments to evaluate model impact on product metrics.
- Experience communicating technical decisions and trade-offs through design documents and postmortems to technical and non-technical stakeholders.
- Preferred: experience driving cross-team ML platform initiatives or modeling standards.
- Preferred: experience with large language models, generative AI, foundation-model fine-tuning, or alignment techniques.
- Preferred: experience building internet-scale recommendation or ranking systems, including feature engineering, retrieval, and scoring pipelines.
- Preferred: experience developing ML observability tooling, dashboards, alerting, and automated anomaly detection.
Benefits
- Bonus, equity, and benefits are included in addition to the stated base salary.
Categories
About Meta
Meta builds social platforms and communication apps—including Facebook, Instagram, WhatsApp, and Messenger—and develops AR/VR hardware and software such as Quest to power immersive computing. It monetizes primarily through advertising tools for businesses, with additional revenue from devices and services, and operates a massive global infrastructure. Founded in 2004 and headquartered in Menlo Park, California, Meta Platforms, Inc. is a public company traded on Nasdaq under the ticker META.