Senior Machine Learning Engineer | Scalable AI Systems

Meta; Burlingame (CA); On-site; USD 184,000 - 257,000; Full time

Benefits offered by this job

Bonus

Equity

Benefits

Job summary

Meta is seeking experienced software engineers to join our machine learning teams in Burlingame, CA, tackling complex problems and building scalable AI-powered products. You will collaborate with product, design, and infrastructure teams, implement advanced interfaces, and mentor peers while driving major initiatives.

Experience with TensorFlow, PyTorch, or Scikit-learn, plus NLP and information retrieval concepts, supports strong impact on efficiency and quality across platforms.

Qualifications

• Bachelor's degree in CS/CE or equivalent practical experience.
• 8+ years of programming experience in a relevant language or 4+ years with a PhD.
• Experience using data and analysis to explain technical problems and provide solutions.

Responsibilities

• Collaborate with cross-functional teams to build innovative application experiences.
• Implement custom user interfaces using latest programming techniques and technologies.
• Analyze and optimize code for quality, efficiency, and performance; provide feedback during code reviews.
• Set direction and goals for teams; lead major initiatives and mentor peers.
• Architect efficient and scalable systems for complex applications.
• Identify and resolve performance and scalability issues; reduce technical debt.
• Work on a variety of coding languages and technologies.
• Establish ownership of components, features, or systems with end-to-end understanding.

Skills

TensorFlow

PyTorch

Scikit-learn

NLP

Data structures

Education

Bachelor's degree in Computer Science, Computer Engineering, or related field

PhD (optional)

Tools

Python

C++

JavaScript

Job description

Meta is seeking experienced software engineers to join our machine learning teams in Burlingame, CA, tackling complex problems and building scalable AI-powered products. You will collaborate with product, design, and infrastructure teams, implement advanced interfaces, and mentor peers while driving major initiatives.

Experience with TensorFlow, PyTorch, or Scikit-learn, plus NLP and information retrieval concepts, supports strong impact on efficiency and quality across platforms.