Senior AI Engineer – Production ML & Recommender Systems

LinkedIn; New York (NY); Hybrid; USD 144,000 - 236,000; Full time

Benefits offered by this job

Stock options

Performance bonus

Benefits

Job summary

LinkedIn is seeking a Senior AI Software Engineer in New York City to own end-to-end machine learning systems at scale. You will shape the recommender and classification stack powering our core products, translating requirements into design and driving experiments across GPU fleets.

This is a senior IC role expected to mentor engineers, align tech direction, and deliver measurable impact. The position uses a hybrid work model with some on-site days in NYC.

Qualifications

• BA/BS Degree in Computer Science, Machine Learning or related technical discipline, or related practical experience.
• 2+ years experience in software design, development, and algorithm related solutions.
• 2+ years experience in programming languages such as Java, Python, etc.
• 2+ years experience with machine learning, data mining, and information retrieval or natural language processing.

Responsibilities

• Own end-to-end machine learning systems running in production at LinkedIn scale.
• Lead the recommender and classification stack powering core products.
• Translate product requirements into system design and drive experiments to prove efficacy.
• Manage GPU fleets and ensure scalable, low-latency inference.

Skills

Machine Learning

Deep Learning

Big Data

Strategic thinking

GAI/LLMs

Education

BA/BS in Computer Science or related

MS or PhD in Computer Science or related

Tools

PyTorch

Spark

AI code development tools (ClaudeCode/Codex/Copilot)

Job description

LinkedIn is seeking a Senior AI Software Engineer in New York City to own end-to-end machine learning systems at scale. You will shape the recommender and classification stack powering our core products, translating requirements into design and driving experiments across GPU fleets.

This is a senior IC role expected to mentor engineers, align tech direction, and deliver measurable impact. The position uses a hybrid work model with some on-site days in NYC.