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Google Certified Machine Learning Engineer Jobs

Zettalogix INC

Machine Learning Engineer

Manhattan, NY · On-site

$126K - $151K/yr

... google cloud certified machine learning engineer Machine Learning Operations Pandas Python Library PySpark Bachelor s or Master s degree in Computer Science, Data Science, Machine Learning ...

New

Givzey

Machine Learning Engineer

Machine Learning Engineer We're looking for a talented and motivated Machine Learning Engineer to ... AWS Certified Machine Learning - Specialty or AWS Certified Big Data - Specialty * Experience with ...

HeyMilo AI

Machine Learning Engineer

Manhattan, NY

Machine Learning Engineer Company: HeyMilo AI Location: New York, NY, USA Contract Details ... AWS or Google Cloud, is a plus - Experience with natural language processing (NLP) and computer ...

Full Scope

Machine Learning Engineer

Reston, VA

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly ... Familiarity with cloud platforms like AWS, Google Cloud, or Azure for model deployment and scaling.

Intraedge

Machine Learning Engineer

Sunrise, FL · Hybrid

Machine Learning Engineer - Generative Al Long term contract Sunrise, FL (Hybrid-3 days onsite ... Strong python, have work experiment on LLM, gen AI, Lang chain, Lang Graph, Python API, Google ...

Prosum Inc.

Machine Learning Engineer

CA · On-site

$75 - $89/hr

Machine Learning Engineer Pay Rate: $75-$89/hour Position Summary We are seeking a skilled Machine ... Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform * Experience with ...

ManTech

Machine Learning Engineer

Herndon, VA

The Machine Learning Engineer will leverage their strong technical background and knowledge to ... Google Cloud Platform (GCP). * Follow Agile methodologies to deliver production-ready, highly ...

ManTech International

Machine Learning Engineer

$128K - $214K/yr

... Google Cloud Platform (GCP). * Follow Agile methodologies to deliver production-ready, highly ... certifications as well as Federal Government Contract Labor categories. In addition, MANTECH ...

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 ...

Leash Bio

Machine Learning Engineer

Salt Lake City, UT

$150K - $200K/yr

Machine Learning Engineer At Leash Biosciences, we are at the cutting edge of integrating machine ... primarily Google Cloud, with flexibility to other platforms). * Collaborate closely with ML ...

Hang

Machine Learning Engineer

New York, NY · On-site +1

... Google, Amazon, Apple, Meta, LinkedIn, Coinbase, Square, and Goldman Sachs. Hang raised a $16 ... About the Role We are seeking a skilled and innovative Machine Learning Engineer to join our team.

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Google Certified Machine Learning Engineer information

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

As of Jun 11, 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

Machine Learning Engineer

Zettalogix INC

Manhattan, NY • On-site

$126K - $151K/yr

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Job: Machine Learning Engineer
Hybrid NYC, NY
Duration: 6+ Months contract

TECHNICAL SKILLS
Must Have
Applied Machine Learning
Azure Databricks
Big Data Analytics
Databricks Certified Data Engineer Associate
Data Structures
google cloud certified machine learning engineer Machine Learning Operations
Pandas Python Library
PySpark
JOB DESCRIPTION
Bachelor s or Master s degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or related field.
Strong experience in machine learning algorithms, predictive modeling, and data mining.
Proficiency in Pyspark, Python pandas (required) for data science workloads.
Strong SQL (required) knowledge and experience with relational databases.
Minimum 3 years of experience with data visualization tools such as Power BI, Dax Queries, and best practices.
Experience with Azure Databricks, Google Cloud, and modern data science libraries (e.g., scikit-learn, pandas, NumPy).
Experience with GenAI and large language models.
Ability to interpret complex datasets and produce actionable insights.
Must know how to analyze the root cause of dashboard errors.
Have experience in ML Ops and have strong coding background.
Have experience with Natural Language Processing (NLP).
Knowledge or experience with A/B Testing.
Working knowledge of designing, training, and implementing machine learning models.
Familiarity with cloud-based infrastructure
Excellent communication and problem-solving skills.
7 or more years of experience in data science and machine learning engineering.
Additional Skills (Skills that are a plus, but not required)
Knowledge of statistical methods and experimental design.
Responsibilities
Key Responsibilities
Advanced Analytics & Machine Learning
Design, develop, and optimize machine learning models (forecasting, classification, clustering).
Apply data mining techniques to uncover patterns and insights in large datasets.
Perform feature engineering, model validation, and performance tuning.
Explore and deploy modern AI and ML approaches to enhance automation and analytics.
Data Preparation & Quality
Prepare structured and unstructured data for modeling and advanced analysis.
Develop scripts and tools for data cleansing, validation, and enrichment.
Collaborate with Data Engineering to maintain efficient data pipelines.
Identify data quality issues and propose remediation.
Analytics, Insights & Reporting
Conduct deep-dive analyses to identify trends and improvement opportunities.
Communicate complex findings in clear, concise ways to technical and non-technical stakeholders.
Support the development of dashboards, metrics, and analytical solutions.
Cross-Team Collaboration
Work with architects, engineers, and analysts to define analytical requirements.
Contribute to conceptual data model design and workflow optimization.
Promote best practices in machine learning, analytics, and data governance.

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