Google

ML Software Engineer, GenAI for Youth

Google$207K — $301K *
Education, Government & Non-Profit
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree or equivalent experience required.
  • 8+ years in software development, system design, or machine learning infrastructure.
  • 8+ years in trust and safety, classification issues, or adversarial machine learning.
  • Familiarity with large-scale data pipelines and high-performance computing.
  • Proven ability to influence and align technical decisions across complex teams.

Responsibilities

  • Develop shared algorithmic frameworks for modeling domains.
  • Streamline engineering efforts by creating cohesive, reusable platform layers.
  • Architect automated evaluation methodologies and benchmarking metrics.
  • Serve as a communication link between multiple engineering and research teams.
  • Advise executive leadership on platform maturity and operational strategies.

Benefits

  • Generous equity opportunities.
  • Performance-based bonus structure.
  • Comprehensive health benefits.
  • Work from collaborative global teams.
  • Opportunity to influence technical decisions at scale.
Full Job Description
Minimum qualifications:
  • Bachelor's degree or equivalent practical experience.
  • 8 years of experience with software development, system design, or machine learning infrastructure.
  • 8 years of experience working with trust and safety, classification problems, large language model (LLM) safety architectures, fraud or risk detection, identity verification, or adversarial machine learning.

Preferred qualifications:
  • Familiarity with industrial-scale data pipelines, internal data orchestration engines, and high-performance compute infrastructure.
  • Demonstrated ability to lead by influence and drive technical alignment across sprawling, matrixed engineering groups without direct operational authority.
  • Exceptional systems-thinking capabilities, with a documented history of transforming fragmented technical processes into highly reusable, automated platform engines.


With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

As a part of the GenAI for Youth, a team within Kids and Families, you will be dedicated to developing the next-generation of scalable, systemically responsible, and high-integrity AI frameworks that power experiences across Google's products. Your mission is to bridge the gap between foundational model research and highly calibrated, age-appropriate production environments.

You will build unified infrastructure that solves complex engineering, user classification, and behavioral modeling challenges once for the entire ecosystem. You will operate across multi-site engineering hubs, establish the technical strategy, algorithmic steering frameworks, and automated validation layers necessary to ensure that Google's AI-driven platform surfaces scale with complete structural accuracy, performance safety, and long-term ecosystem health.The Core team builds the technical foundation behind Google's flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google's products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $301000 (USD) 20% bonus target equity benefits

Learn more about benefits at Google .

Responsibilities
  • Develop shared algorithmic frameworks and foundational math in core modeling domains, including runtime behavior steering, latent-space pattern detection, optimization loops, and fine-tuning rooted in industry best practices.
  • Streamline engineering efforts across global product lines by shifting fragmented, application-specific pipelines into cohesive, highly scalable, and reusable platform layers.
  • Architect definitive, automated evaluation methodologies and standardized benchmarking metrics to provide scientifically rigorous validation models, eliminating manual execution overhead.
  • Serve as a technical conduit between product, data science, applied engineering groups, machine learning research organizations, and centralized core infrastructure teams.
  • Act as a strategic advisory partner to executive engineering leadership on platform maturity, long-term technical debt reduction, and operational capacity across technical workstreams.


About Google

Google is a multinational technology company that specializes in Internet-related services and products. These include online advertising technologies, search engine, cloud computing, software, and hardware. Google was founded in 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University. The company has grown tremendously since then and has become one of the most valuable companies in the world. Google's mission is to organize the world's information and make it universally accessible and useful.
Learn more about Google
Size
156,500 employees
Market Cap
$1,115.4 billion
Industry
Net Income
$40.2 billion
Founded
1998
5 Year Trend
+23.3%
Revenue
$182.5 billion
NASDAQ

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