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Director Google Machine Learning Engineer Jobs in Ohio

Google AI Lead Architect

Cincinnati, OH · On-site

$54 - $74/hr

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

Google AI Lead Architect

Columbus, OH · On-site

$53.25 - $73.25/hr

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

Statistics, Analytics, Data Science, Engineering, Operations Research, Economics, Mathematics ... Prior experience with public cloud technologies such as Amazon Web Services(AWS), Azure or Google ...

AI Solutions Architect

Columbus, OH · On-site

$60.75 - $80.25/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

AI Solutions Architect

Cincinnati, OH

$60.50 - $79.75/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

AI Solutions Architect

Cleveland, OH · On-site

$61 - $80.50/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Akron, OH · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

DUTIES & RESPONSIBILITIES Design and develop machine learning and deep learning models for real ... Azure, or Google Cloud) Knowledge of RESTful APIs and microservices architecture PREFERRED ...

New

DUTIES & RESPONSIBILITIES · Design and develop machine learning and deep learning models for real ... or Google Cloud) · Knowledge of RESTful APIs and microservices architecture PREFERRED ...

New

DUTIES & RESPONSIBILITIES • Design and develop machine learning and deep learning models for real ... or Google Cloud) • Knowledge of RESTful APIs and microservices architecture PREFERRED ...

New

Responsibilities : • Design and develop machine learning and deep learning models for real-world ... Google Cloud) • Knowledge of RESTful APIs and microservices architecture Preferred : • ...

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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 Ohio? The most popular types of Google Machine Learning Engineer jobs in Ohio are:
What are popular job titles related to Director Google Machine Learning Engineer jobs in Ohio? For Director Google Machine Learning Engineer jobs in Ohio, the most frequently searched job titles are:
What cities in Ohio are hiring for Director Google Machine Learning Engineer jobs? Cities in Ohio with the most Director Google Machine Learning Engineer job openings:
Infographic showing various Director Google Machine Learning Engineer job openings in Ohio as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 16% Part Time, 1% Temporary, and 1% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.
Google AI Lead Architect

Google AI Lead Architect

Deloitte

Cincinnati, OH • On-site

$54 - $74/hr

Full-time

This job post has expired today. Applications are no longer accepted.


Deloitte rating

8.0

Company rating: 8.0 out of 10

Based on 89 frontline employees who took The Breakroom Quiz

72nd of 146 rated financial services


Job description

Job Summary:
Deloitte is seeking a Google AI Lead Architect to join their AI & Engineering team, focusing on transforming technology platforms and driving innovation for clients. The role involves architecting and delivering enterprise AI platforms on Google Cloud, optimizing for scalability, reliability, and security.
Responsibilities:
• Architect and Design: Lead the design and development of enterprise-grade AI applications and platforms, with a focus on scaling AI solutions for production. This includes defining the technical architecture, selecting appropriate technologies, and ensuring solutions are robust, scalable, and secure.
• LLM and AI Integration: Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and monitoring, with an emphasis on production-level performance and reliability.
• Enterprise Architecture: Collaborate with enterprise architects to ensure AI solutions align with the broader company's technical strategy, governance, and standards.
• Cloud and GenAI Native Development: Design and deploy applications using Cloud Native principles on a hyperscaler platform (AWS, Azure, GCP). Leverage a wide range of hyperscaler tools and services, including containers (Docker, Kubernetes), serverless functions, and managed databases. Should have experience in leveraging various GenAI tools to accelerate software development life cycle.
• Security & Governance: Ensure the security of all AI/ML systems by addressing potential vulnerabilities such as data privacy concerns, model poisoning, and adversarial attacks.
• Design Patterns: Apply and enforce Application Design Patterns and Agentic Design Patterns to build resilient and maintainable software systems.
Qualifications:
Required:
• Bachelor's degree in Computer Science, Engineering or a related technical field.
• 8+ years' experience as a Software or Solution Architect, with a strong focus on application development and scaling solutions for production environments.
• 5+ years hands-on with Google Cloud, including 2+ end-to-end enterprise implementations in production.
• 4+ years designing and implementing Google Cloud networks, security controls, and landing zones using Terraform.
• 3+ years building and operating containerized workloads on GKE (autoscaling, ingress, monitoring/observability).
• 3+ years implementing CI/CD and DevSecOps with Cloud Build, GitHub Actions, or Jenkins.
• 3+ years executing migration or modernization programs to Google Cloud (rehost, replatform, refactor).
• 2+ years applying AI/GenAI on Google Cloud with Vertex AI and Gemini, including 1+ years' production deployment (e.g. RAG with Vertex AI Search/Vector Search, prompt design, safety policies, observability).
• Deep understanding of AI/ML concepts, including experience with LLMs and their application in enterprise settings.
• Experience implementing multiple AI solutions in a professional, real-world environment.
• Strong understanding of security implications related to AI/ML systems (e.g., data privacy, model poisoning, adversarial attacks).
• Familiarity with various hyperscaler tools and services.
• Hyperscaler Architect certification is required (e.g., AWS Certified Solutions Architect, Azure Solutions Architect Expert, or GCP Professional Cloud Architect).
• Ability to travel up to 50% based on the work you do and the clients and industries/sectors you serve.
Preferred:
• Google Professional Machine Learning Engineer certification or the equivalent ML certification.
• Master's degree in technology-related discipline.
• 2+ years' leading high performance, results driven engineering teams delivering AI platforms or applications.
• 1+ year implementing LLMOps/MLOps using Vertex AI Pipelines and Cloud Build (or similar)
Company:
Deloitte is a business consulting company that offers audit, consulting, financial advisory, and tax services. Founded in 1845, the company is headquartered in London, GBR, with a team of 10001+ employees. The company is currently Late Stage.

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