Staff Software Engineer, AI/ML, Cloud IAM, Dataset and Model Training

Responsibilities

You will design and scale ML training data pipelines and optimize models for intelligent IAM, focusing on access-risk scoring and anomaly detection. Additionally, you will partner with security engineers to identify edge cases and establish evaluation benchmarks to ensure model reliability.

Requirements

Candidates must have at least 8 years of software development experience, including 5 years in ML design and optimization. A bachelor's degree is required, with a preference for a master's or PhD in a technical field.

Skills

• Machine Learning
• Software Development
• Python
• PyTorch
• JAX
• Cloud Security
• Data Pipelines
• Risk Scoring
• Anomaly Detection
• System Architecture
• Reinforcement Learning
• Transformers
• Feature Engineering
• Model Training
• IAM
• Distributed Computing

Benefits

• Bonus
• Equity
• Health Insurance

About this role

MINIMUM QUALIFICATIONS:

* Bachelor’s degree or equivalent practical experience.
* 8 years of experience in software development.
* 5 years of experience testing, and launching software products, and 3 years
of experience with software design and architecture.
* 5 years of experience with one or more of the following: Speech/audio (e.g.,
technology duplicating and responding to the human voice), reinforcement
learning (e.g., sequential decision making), ML infrastructure, or
specialization in another ML field.
* 5 years of experience leading ML design and optimizing end-to-end Machine
Learning (e.g., model deployment, model evaluation, data processing,
debugging, fine tuning).

PREFERRED QUALIFICATIONS:

* Master’s degree or PhD in Engineering, Computer Science, or a related
technical field.
* 8 years of experience with data structures and algorithms.
* 3 years of experience in a technical leadership role leading project teams
and setting technical direction.
* 8 years of experience training, fine-tuning, and evaluating machine learning
and deep learning models in Python (e.g., PyTorch, JAX, scikit-learn,
GBDTs/XGBoost, or Transformers).
* Experience with dataset curation, feature engineering, synthetic data
generation, and building reproducible ML training and evaluation pipelines at
scale.
* Experience developing ranking, retrieval, classification, or risk/anomaly
scoring models for production systems.

ABOUT THE JOB:

Google's software engineers develop the next-generation technologies that change
how billions of users connect, explore, and interact with information and one
another. Our products need to handle information at massive scale, and extend
well beyond web search. We're looking for engineers who bring fresh ideas from
all areas, including information retrieval, distributed computing, large-scale
system design, networking and data storage, security, artificial intelligence,
natural language processing, UI design and mobile; the list goes on and is
growing every day. As a software engineer, you will work on a specific project
critical to Google’s needs with opportunities to switch teams and projects as
you and our fast-paced business grow and evolve. We need our engineers to be
versatile, display leadership qualities and be enthusiastic to take on new
problems across the full-stack as we continue to push technology forward.

The Cloud IAM team builds foundational authorization and policy intelligence
systems securing Google Cloud Platform for enterprise customers, workloads, and
AI agents. You will build core ML models and data pipelines transforming Cloud
IAM from a static access control system into an adaptive, risk-aware
intelligence engine. Combining dataset engineering and model training expertise
with cloud security and reliability focus, you will design scalable data
pipelines, train compact risk-scoring models, and integrate explainable ML
predictions with deterministic security guardrails. Your systems will evaluate
access risk in real time, recommend least-privilege policies, detect risky
permission combinations, and help security administrators automate access
decisions safely and efficiently.

Individual pay is determined by factors including job-related skills,
experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google
[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

* Design and scale training data pipelines using access telemetry, policy
graphs, and synthetic data with rigorous de-noising.
* Train and optimize ML models for Intelligent IAM, focusing on access-risk
scoring, anomaly detection, and least-privilege recommendations.
* Build explainability and calibration layers to provide clear reasoning for
risk scores, routing uncertain cases to human review or static rules.
* Partner with security engineers to identify IAM edge cases, ensuring models
learn subtle privilege boundaries without over-granting access.
* Establish evaluation benchmarks and online monitoring to prevent model drift,
and optimize models for low-latency Google Cloud serving.

About Google

Software Development · 10,001+ employees · headquartered in Mountain View, CA