AI Engineer

LinkedIn•Mountain View, CA

18h•Hybrid

About The Position

AI is at the core of how LinkedIn connects more than a billion members to opportunity across jobs, sales, marketing, content, and trust platforms. As an AI Software Engineer you will own end-to-end machine learning systems that run in production at LinkedIn scale. You won't just train models, you will own the recommender and classification system that power LinkedIn’s core products. Your responsibilities cover the full product lifecycle from translating product requirements into system design, training the models to power the system, driving the experiments that prove efficacy, and managing the GPU fleets that run them at scale in milliseconds; you are the engine that drives value for our members. This is an individual-contributor role; we expect you to be the owner of a well-defined significant workstream, align technical direction within your team, review code and technical designs from your team, and to deliver measurable member and business impact with a sense of urgency.

Requirements

Bachelor's degree in Computer Science or related technical field or equivalent technical experience
1+ years experience with machine learning, data mining, and information retrieval or natural language processing
1+ year of industry experience in software design, development, and algorithm related solutions.
1+ years experience in programming languages such as Java, Python, etc.

Nice To Haves

2+ years of relevant AI/Machine Learning experience.
MS in Computer Science or related technical discipline
Experience with PyTorch or similar Deep Learning frameworks
Experience with Spark for data manipulation and transformation
Experience with A/B testing at scale in a consumer-facing product
Experience with AI code development (i.e ClaudeCode, Codex, Copilot)
Experience adapting pre-trained LLMs to production systems including fine-tuning and student-teacher model paradigms
Published work in academic conferences or industry circles.

Responsibilities

Own end-to-end machine learning systems that run in production at LinkedIn scale.
Own the recommender and classification system that power LinkedIn’s core products.
Translate product requirements into system design.
Train models to power the system.
Drive experiments that prove efficacy.
Manage the GPU fleets that run them at scale in milliseconds.
Be the owner of a well-defined significant workstream.
Align technical direction within your team.
Review code and technical designs from your team.
Deliver measurable member and business impact with a sense of urgency.
Grow to the owner of an AI workstream end to end and ship at least one model-based system to a measured impact on member or business value.
Become the go-to point of contact for your domain within our team and help others onboard to it as needed.
Implement an efficiency or quality improvement (i.e. inference/training efficiency, engineer velocity, or tech-debt removal) backed by data.
Operate systems reliably as on-call and work with senior engineers to root-cause at least one significant production regression.