ZipRecruiter

Log In

1

Director Google Machine Learning Engineer Jobs in Arizona

Programmers.io

AI/ML Engineer

Scottsdale, AZ · On-site

Google Cloud Professional Machine Learning Engineer Google Cloud Professional Data Engineer AWS Certified Machine Learning Specialty Certified Kubernetes Admin(CKA) Google Professional Cloud ...

Deloitte

Google AI Lead Architect

Tempe, AZ · On-site

$53.75 - $73.75/hr

Preferred : • Google Professional Machine Learning Engineer certification or the equivalent ML certification. • Master's degree in technology-related discipline. • 2+ years' leading high ...

next page

Showing results 1-20

All JobsGoogle Machine Learning Engineer JobsDirector Google Machine Learning Engineer JobsDirector Google Machine Learning Engineer Jobs in Arizona

Director Google Machine Learning Engineer information

Is L7 senior at Google?

At Google, L7 is considered a senior-level position, typically involving significant technical expertise and leadership responsibilities. It is often associated with senior engineers or managers, depending on the role and team structure.

What engineer makes $500,000 a year?

A senior Google Machine Learning Engineer or Director level in large tech companies can earn $500,000 or more annually, often including base salary, bonuses, and stock options. These roles typically require extensive experience, advanced skills in machine learning and AI, and often involve leadership responsibilities and high-impact projects.

How much does a Google Engineering director make?

A Google Engineering Director typically earns between $200,000 and $300,000 annually, with total compensation including bonuses and stock options often exceeding this range. Compensation varies based on experience, location, and performance, and senior roles may include additional benefits and incentives.

Will MLE be replaced by AI?

As a Google Machine Learning Engineer, the role involves developing and deploying AI models, but AI is a tool that enhances rather than replaces MLE work. MLEs focus on designing, optimizing, and maintaining machine learning systems, which require expertise in data science, programming, and domain knowledge that AI cannot fully replicate. The role is expected to evolve with advancements in AI, emphasizing collaboration with AI systems rather than replacement.
What are the most commonly searched types of Google Machine Learning Engineer jobs in Arizona? The most popular types of Google Machine Learning Engineer jobs in Arizona are:
What are popular job titles related to Director Google Machine Learning Engineer jobs in Arizona? For Director Google Machine Learning Engineer jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Director Google Machine Learning Engineer jobs in Arizona look for? The top searched job categories for Director Google Machine Learning Engineer jobs in Arizona are:
What cities in Arizona are hiring for Director Google Machine Learning Engineer jobs? Cities in Arizona with the most Director Google Machine Learning Engineer job openings:
Director Google Machine Learning Engineer jobs near you
AI/ML Engineer

AI/ML Engineer

Programmers.io

Scottsdale, AZ • On-site

Contractor

Re-posted 3 days ago

Job description

Key Responsibilities:
Design, implement, and maintain ML pipelines for training, testing, and deploying AIML models.
Manage and optimize cloud-based ML infrastructure (GCP Vertex AI, AWS SageMaker, or equivalent).
Implement CICD pipelines for ML and AI-driven applications.
Monitor, troubleshoot, and optimize model performance and system reliability.
Automate workflows for data ingestion, model training, deployment, and monitoring.
Collaborate with cross-functional teams to ensure secure, scalable, and compliant ML operations.
Apply MLOps best practices for reproducibility, versioning, and governance of ML models.
Required Qualifications:
5 years experience in DevOps, CloudOps, or ML Ops.
5 years experience with GCP AIML services (Vertex AI, AI Platform, BigQuery ML) or AWS ML services (SageMaker etc).
5 years Experience with containerization and orchestration (Docker, Kubernetes).
Proficiency in infrastructure-as-code (Terraform, CloudFormation, or Deployment Manager). Familiarity with CICD pipelines (Jenkins, GitHub Actions, GitLab CI, or ArgoCD).
Strong programming skills in Python, Bash, or Go, with experience in ML frameworks (TensorFlow, PyTorch, Scikit-learn).
Preferred Certifications (one or more):
Google Cloud Professional Machine Learning Engineer
Google Cloud Professional Data Engineer
AWS Certified Machine Learning Specialty
Certified Kubernetes Admin(CKA)
Google Professional Cloud Architect