Google Senior Software Engineer – AI/ML (Ads and Commerce)

Opportunity Overview

Role Scope & Technical Architecture

The Ads and Commerce team develops scalable AI/ML solutions, leveraging Gemini models, Retrieval Augmented Generation (RAG), and Google ML infrastructure to power advertiser workflows, merchant experiences, and ad recommendation platforms:

[Merchant/User Intent Data] ➔ [Vector Search & RAG Retrieval] ➔ [Gemini Fine-Tuning & Ingestion] ➔ [Real-Time Ad/Commerce APIs]

Core Responsibilities

• Generative AI & RAG Solutions: Design and implement features leveraging Gemini models, vector search, embedding optimization, and semantic retrieval strategies for sellers and advertisers.

• ML Infrastructure & Pipelines: Build scalable data processing pipelines, real-time APIs, model evaluation frameworks, and deployment engines for high-throughput commercial applications.

• Test-Driven Engineering: Develop, launch, and maintain production features using a Test-Driven Development (TDD) approach across distributed systems.

• Cross-Functional Leadership: Partner with Product Managers, UX Designers, Business Leaders, and core engineering teams to shape commercial AI features.

Candidate Eligibility & Technical Skills Matrix

Minimum Qualifications

• Education: Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.

• Software Development: 5+ years of software development experience across one or more primary programming languages (e.g., C++, Java, Python, Go).

• System Architecture & Lifecycle: 3+ years testing, maintaining, or launching software products, plus 1+ year of formal software design and system architecture experience.

• Specialised ML Experience: 3+ years in speech/audio, reinforcement learning, or a specialised ML field.

• ML Infrastructure & GenAI: 3+ years of experience in model deployment, evaluation, optimisation, data processing, and debugging, alongside hands-on Generative AI experience.

Preferred Qualifications

Compensation & Benefits Structure (USA)

• Base Salary Range: $174,000 – $252,000 USD per year (determined by experience, skills, and level).

• Bonus Target: 15% annual target bonus.

• Equity Compensation: Google Equity (Restricted Stock Units) subject to vesting schedules.

• Benefits Package: Health/dental/vision plans, 401(k) matching, wellness resources, on-site campus amenities, and relocation support (where applicable).

Selection Workflow & Evaluation Stages

[Resume & Profile Screening] ➔ [Recruiter Phone Screen] ➔ [Technical Phone Screen] ➔ [Virtual Onsite Loop (5 Rounds)]

1. Recruiter Screening: Initial discussion covering ML background, experience with Generative AI/RAG architectures, and career history.

2. Technical Phone Screen: Live coding and algorithmic problem-solving session in C++, Java, Python, or Go.

3. Virtual Onsite Loop:

   • Coding & Data Structures (2 Rounds): Advanced algorithms, memory management, and code efficiency under constraint.

   • ML System Design (1 Round): Designing an end-to-end Machine Learning system (e.g., ad retrieval engine, vector search infrastructure, or Gemini-powered feature execution).

   • Distributed Systems Architecture (1 Round): Designing high-throughput, low-latency microservices handling enterprise query volumes.

   • Googleyness & Leadership (1 Round): Behavioural evaluation focused on team leadership, cross-functional collaboration, ownership, and adaptability