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Google Certified Machine Learning Engineer Jobs

Ontrac Solutions

Machine Learning Engineer

Chicago, IL · On-site

$70 - $90/hr

This role is ideal for junior-to-mid-level engineers with strong Google Cloud Platform experience and a focus on building, maintaining, and supporting production-grade machine learning systems. The ...

Ontrac Solutions LLC

Machine Learning Engineer

Chicago, IL · On-site

$70 - $90/hr

This role is ideal for junior-to-mid-level engineers with strong Google Cloud Platform experience and a focus on building, maintaining, and supporting production-grade machine learning systems. The ...

Stefanini

Machine Learning Engineer

Dearborn, MI

Hands-on experience with Google Cloud Platform (Google Cloud Platform) services relevant to AI/ML. Basic understanding and practical experience with Machine Learning model fine-tuning. Familiarity ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... Google Cloud AI Platform * Docker * Kubernetes * MLflow * CI/CD pipelines * Model Deployment ...

Ontrac Solutions

Machine Learning Engineer

Chicago, IL

$70 - $90/hr

This role is ideal for junior-to-mid-level engineers with strong Google Cloud Platform experience and a focus on building, maintaining, and supporting production-grade machine learning systems. The ...

Cymertek

Machine Learning Engineer

Aurora, CO · On-site

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Inizio Partners

Machine Learning Engineer (GCP)

Manhattan, NY · Remote

$58.25 - $79.75/hr

As a GCP ML Engineer, you'll design, develop, and maintain machine learning pipelines and infrastructure on the Google Cloud Platform (GCP). You'll work closely with data scientists, engineers, and ...

Cymertek

Machine Learning Engineer

Vienna, VA

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... Google Cloud AI Platform * Docker * Kubernetes * MLflow * CI/CD pipelines * Model Deployment ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... Google Cloud AI Platform * Docker * Kubernetes * MLflow * CI/CD pipelines * Model Deployment ...

Cymertek

Machine Learning Engineer

Reston, VA

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Cymertek

Machine Learning Engineer

Honolulu, HI · On-site

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Cymertek

Machine Learning Engineer

Aurora, CO

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

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All JobsGoogle Certified Machine Learning Engineer Jobs

Google Certified Machine Learning Engineer information

See salary details

$15

$62

$88

How much do google certified machine learning engineer jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for google certified machine learning engineer in the United States is $62.98, according to ZipRecruiter salary data. Most workers in this role earn between $53.61 and $70.91 per hour, depending on experience, location, and employer.

Is GCP ML engineer certification worth it?

The GCP Machine Learning Engineer certification validates skills in designing and deploying ML models on Google Cloud Platform, which can enhance job prospects and demonstrate technical expertise. It is recognized by employers as a valuable credential for roles involving cloud-based machine learning and data engineering.

Can I actually get a job with a Google certificate?

A Google Certified Machine Learning Engineer credential can enhance your resume and demonstrate proficiency in machine learning concepts, tools, and Google Cloud Platform services. While certification alone does not guarantee a job, it can improve your chances by validating your skills to employers and complementing practical experience and a strong portfolio.

What are the key skills and qualifications needed to thrive as a Google Certified Machine Learning Engineer, and why are they important?

To thrive as a Google Certified Machine Learning Engineer, you need a solid background in computer science, statistics, and applied mathematics, typically supported by experience in designing and deploying machine learning models. Mastery of tools such as TensorFlow, Python, Google Cloud Platform (GCP), and the relevant Google ML Engineer certification is usually required. Strong problem-solving abilities, communication skills, and a collaborative mindset help you translate complex models into actionable business solutions and work effectively with stakeholders. These competencies are critical for building scalable, impactful machine learning systems that drive innovation and deliver value in real-world applications.

What is the difference between Google Certified Machine Learning Engineer vs Data Scientist?

AspectGoogle Certified Machine Learning EngineerData Scientist
CertificationsGoogle Cloud Certified Professional Machine Learning EngineerOften no specific certification required, but certifications like Google Data Analytics or Python are common
Work EnvironmentFocus on deploying ML models on Google Cloud, working with cloud toolsData analysis, statistical modeling, and visualization, often in various environments
Industry UsagePrimarily in tech, cloud services, AI developmentBroadly across finance, healthcare, marketing, and tech

The Google Certified Machine Learning Engineer specializes in deploying and managing ML models on Google Cloud, often requiring specific cloud certifications. Data Scientists focus on analyzing data, building models, and deriving insights across various industries, with less emphasis on cloud deployment. Both roles overlap in data handling and modeling but differ in their primary focus and required credentials.

What are Google Certified Machine Learning Engineers?

Google Certified Machine Learning Engineers are professionals who have demonstrated proficiency in designing, building, and deploying machine learning models using Google Cloud technologies. They are certified through Google’s rigorous exam, which assesses skills in data preparation, model development, productionalization, and responsible AI practices. These engineers are equipped to solve real-world business problems using advanced machine learning techniques and Google Cloud tools. Earning this certification validates expertise and can enhance career opportunities in the rapidly growing field of machine learning.

What types of projects do Google Certified Machine Learning Engineers typically work on within a team setting?

Google Certified Machine Learning Engineers often collaborate with data scientists, software engineers, and product managers to design, implement, and deploy machine learning models. Their projects can include developing recommendation systems, automating data analysis, or improving business processes through predictive analytics. They are usually responsible for ensuring model accuracy, scalability, and integration into existing systems, while also participating in code reviews and knowledge sharing sessions. This collaborative environment fosters both technical growth and cross-functional learning.

What engineers make $500,000?

Senior machine learning engineers, especially those with extensive experience, advanced certifications like Google Certified Machine Learning Engineer, and expertise in tools such as TensorFlow or PyTorch, can earn $500,000 or more annually. Compensation varies based on industry, location, company size, and individual skill level.

What is the salary of an aiml engineer in Google?

A Google Certified Machine Learning Engineer typically earns between $120,000 and $180,000 annually, depending on experience, location, and level within the company. Salaries may also include bonuses, stock options, and other benefits, reflecting the competitive nature of tech industry compensation.
Infographic showing various Google Certified Machine Learning Engineer job openings in the United States as of June 2026, with employment types broken down into 2% As Needed, 94% Full Time, 2% Part Time, and 2% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $131,001 per year, or $63 per hour.

Machine Learning Engineer

Ontrac Solutions

Chicago, IL • On-site

$70 - $90/hr

Full-time

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

Job description

Ontrac Solutions is seeking Machine Learning Engineers to support an urgent staff augmentation engagement for one of our clients.

This role is ideal for junior-to-mid-level engineers with strong Google Cloud Platform experience and a focus on building, maintaining, and supporting production-grade machine learning systems.

The selected engineers will work under the direct guidance of a Staff ML Architect and will focus heavily on daily MLOps execution, pipeline maintenance, model reliability, and production support for a high-traffic digital platform.

Required Credentials
  • 2+ years of experience in machine learning engineering, data engineering, software engineering, or a related technical role.
  • Hands-on experience supporting production or near-production ML systems.
  • Bachelor's degree in Computer Science, Engineering, Data Science, Machine Learning, or equivalent practical experience.
Required Qualifications
  • Solid hands-on experience with the GCP ecosystem, particularly Vertex AI components such as Workbench, Pipelines, and Model Registry.
  • Proficiency with modern ML frameworks, including PyTorch or similar technologies.
  • Experience with containerization tools, especially Docker, for automated builds and deployments.
  • Practical experience managing data processing workflows using Apache Spark and Airflow.
  • Understanding of MLOps best practices, including model deployment, monitoring, training workflows, inference support, and pipeline reliability.
  • Familiarity with real-time model serving and infrastructure tools such as Triton Inference Server and Terraform is highly preferred.
  • Strong problem-solving skills with the ability to troubleshoot, maintain, and optimize ML pipelines in a production environment.
  • Collaborative mindset with the ability to execute technical tasks reliably under the guidance of a senior architect.
Key Responsibilities
  • Support the design, deployment, monitoring, and maintenance of machine learning models in a high-traffic production environment.
  • Maintain, troubleshoot, and optimize end-to-end ML pipelines from raw data ingestion through offline and online model evaluation.
  • Execute daily MLOps tasks, including model training, inference support, pipeline monitoring, and deployment maintenance.
  • Work with tools such as GCP, Vertex AI, Spark, Airflow, Docker, PyTorch, and related MLOps technologies.
  • Build and manage automated containerized deployments to support continuous model operations.
  • Partner closely with the Staff ML Architect and other ML Engineers to ensure models are reliable, scalable, and production-ready.
  • Help identify and resolve performance, reliability, and scalability issues across ML workflows and infrastructure.
Preferred Qualifications
  • Prior experience supporting high-traffic digital platforms or consumer-facing products.
  • Experience with Triton Inference Server, Terraform, or similar infrastructure and real-time serving tools.
  • Experience working in staff augmentation, consulting, or fast-moving client-facing environments.
  • Strong interest in building reliable, production-grade ML systems rather than only experimental or research-focused models.
About Ontrac Solutions

Ontrac Solutions is a strategic consulting and technology solutions firm helping companies Innovate. Create. Elevate. through digital product consulting, cloud solutions, AI-based data solutions, and staff augmentation.

We partner with clients to bring the right technical expertise, execution support, and strategic guidance to complex business and technology initiatives.