Senior AI/ML Engineer - LLMs, RL & Production ML

Socket.dev; Mountain View (CA); On-site; USD 174,000 - 252,000; Full time

Benefits offered by this job

15% bonus target

Equity

Benefits

Job summary

Google is seeking software engineers to advance next-generation ML models and AI-driven ad systems. You will design production-ready ML solutions, collaborate with researchers and product teams, and drive end-to-end ML lifecycles from concept to launch.

The role emphasizes translating novel ideas in LLMs, RL, and agentic systems into scalable features while contributing to research publications and maintaining high-traffic, latency-critical production systems.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 2 years of experience in large language model (LLM) modeling, including pre-training or fine-tuning.
• 2 years of experience with Generative AI technologies, and launching features.

Responsibilities

• Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.
• Design, build, and productionize sophisticated machine learning models to understand user intent and advertiser objectives.
• Collaborate closely with Research Scientists and Product teams to translate novel concepts in LLMs, RL, and agentic systems from initial prototypes into scalable, production-ready solutions.
• Take ownership of the end-to-end ML lifecycle to develop and launch new advertising products.
• Contribute to the scientific community with opportunities to co-author publications for academic conferences (e.g., NeurIPS, ICML).

Skills

Software development

LLM modeling

Generative AI

Data structures & algorithms

Reinforcement Learning

Publication record

Education

Bachelor's degree

PhD in CS/AI/ML

Job description

Google is seeking software engineers to advance next-generation ML models and AI-driven ad systems. You will design production-ready ML solutions, collaborate with researchers and product teams, and drive end-to-end ML lifecycles from concept to launch.

The role emphasizes translating novel ideas in LLMs, RL, and agentic systems into scalable features while contributing to research publications and maintaining high-traffic, latency-critical production systems.