Senior Machine Learning Infrastructure Engineer, Embedding Platform

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and enhance large-scale machine learning platforms tailored for recommendation or personalization systems.

• Take ownership of significant components of ML systems from initial problem definition to final production deployment.

• Construct and refine comprehensive ML pipelines that include data preparation, feature creation, model training, evaluation, and deployment.

• Enhance distributed training processes, improve model efficiency, and boost online inference performance.

• Utilize contemporary modeling techniques, including sequence modeling and related foundational model strategies, for Reddit applications.

• Establish dependable serving and monitoring protocols for production ML systems that demand low latency and high throughput.

• Collaborate with cross-functional teams in product, relevance, advertising, and core ML to achieve tangible enhancements in user experience and business outcomes.

• Conduct thorough offline and online evaluations, including experimentation, model diagnostics, and improvement of feedback loops.

• Contribute to engineering excellence through high-quality code, design reviews, comprehensive documentation, and operational best practices.

⛳️ Requirements

• Over 5 years of experience in machine learning engineering, concentrating on large-scale ML infrastructure and recommendation or personalization systems.

• Proficient in modern deep learning architectures, including sequence models and foundational models.

• Proven experience in building or scaling ML platforms for extensive datasets and high-traffic production settings.

• Capability to independently define and execute ambiguous technical projects while ensuring high-quality implementation details.

• Strong comprehension of distributed training and inference principles, encompassing data parallelism, model parallelism, and pipeline parallelism.

• Expertise in Python and familiarity with contemporary ML frameworks like PyTorch, TensorFlow, or similar.

• Robust foundation in software engineering principles, including system design, debugging, testing, and performance enhancement.

• Experience with A/B testing, model evaluation frameworks, and real-time feedback mechanisms in large-scale production environments.

• Exceptional communication skills to convey intricate ML concepts to both technical and non-technical audiences.

🏝️ Benefits

• Comprehensive Healthcare Benefits and Income Replacement Programs

• 401k with Employer Match

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support

• Family Planning Support

• Gender-Affirming Care

• Mental Health & Coaching Benefits

• Flexible Vacation & Paid Volunteer Time Off

• Generous Paid Parental Leave

• Equity in the form of restricted stock units

• Medical, dental, and vision insurance

• Generous time off for vacation

• Parental leave