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Google Cloud Machine Learning Engineer Jobs in New Jersey

Chefman

Machine Learning Engineer

Mahwah, NJ · On-site

As a Machine Learning Engineer, you will play a critical role in shaping the future of cooking ... Experience working with public cloud platforms such as AWS, Google Cloud Platform, or Microsoft ...

AvePoint

Senior Machine Learning Engineer

Jersey City, NJ · On-site

$190K - $220K/yr

... Microsoft, Google, Salesforce, and other collaboration environments. AvePoint's global channel ... cloud marketplaces. To learn more, visit www.avepoint.com . At AvePoint, we are committed to ...

1Kosmos

AI / Machine Learning Engineer

Iselin, NJ · On-site

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer ... Implement model optimization techniques for mobile (on-device) and cloud inference. * Apply fraud ...

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Google Cloud Machine Learning Engineer information

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$23

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

As of Sep 1, 2026, the average hourly pay for google cloud machine learning engineer in New Jersey is $63.84, according to ZipRecruiter salary data. Most workers in this role earn between $54.42 and $72.74 per hour, depending on experience, location, and employer.

What is a Google Cloud Machine Learning engineer?

Google Cloud Machine Learning Engineers are professionals who design, build, and deploy machine learning models using Google Cloud Platform (GCP) services and tools. They work with large datasets, develop scalable ML solutions, and collaborate with data scientists and software engineers. Their role often includes automating data pipelines, optimizing model performance, and ensuring the reliability and security of ML deployments on the cloud. These engineers have expertise in both machine learning algorithms and cloud infrastructure, making them key contributors to data-driven projects.

What are the key skills and qualifications needed to thrive as a Google Cloud Machine Learning engineer?

To thrive as a Google Cloud Machine Learning Engineer, you need strong programming skills in Python or Java, a deep understanding of machine learning algorithms, and a degree in computer science or a related field. Familiarity with Google Cloud Platform (GCP) services such as Vertex AI, BigQuery, TensorFlow, and relevant certifications like the Professional Machine Learning Engineer certification is highly valuable. Excellent problem-solving abilities, collaboration, and clear communication make someone stand out in this position. These skills and qualities are critical for designing, deploying, and optimizing scalable ML solutions that meet business objectives in cloud environments.

What are some typical cross-functional collaborations for a Google Cloud Machine Learning engineer?

As a Google Cloud Machine Learning Engineer, you'll frequently work alongside data scientists, software engineers, and product managers to design, deploy, and maintain machine learning solutions at scale. Collaboration often involves translating business requirements into machine learning pipelines, integrating models into cloud-based applications, and ensuring that solutions are robust, secure, and scalable. Regular communication with DevOps and infrastructure teams is also common to optimize model deployment and monitor performance. This cross-disciplinary teamwork is crucial for delivering impactful, production-ready AI solutions.

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

AspectGoogle Cloud Machine Learning EngineerData Scientist
Required CredentialsGoogle Cloud certifications, programming skills, ML knowledgeStatistics, data analysis, programming, often with advanced degrees
Work EnvironmentCloud platforms, coding, deploying ML modelsData analysis, modeling, reporting, often in research or business settings
Employer & Industry UsageTech companies, cloud service providers, enterprises using Google CloudVarious industries including finance, healthcare, marketing, research

Google Cloud Machine Learning Engineers focus on developing and deploying ML models on Google Cloud, requiring cloud certifications and coding skills. Data Scientists analyze data, build models, and generate insights, often with advanced degrees. While both roles work with data and ML, the Engineer role emphasizes cloud deployment and infrastructure, whereas Data Scientists focus on data analysis and modeling.

What are popular job titles related to Google Cloud Machine Learning Engineer jobs in New Jersey?

For Google Cloud Machine Learning Engineer jobs in New Jersey, the most frequently searched job titles are:

What job categories do people searching Google Cloud Machine Learning Engineer jobs in New Jersey look for?

The top searched job categories for Google Cloud Machine Learning Engineer jobs in New Jersey are:

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Cities in New Jersey with the most Google Cloud Machine Learning Engineer job openings:

Google Cloud Machine Learning Engineer jobs near you
Infographic showing various Google Cloud Machine Learning Engineer job openings in New Jersey as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $132,795 per year, or $63.8 per hour.

Machine Learning Engineer GCP Vertex AI Apache Iceberg

Whippany, NJ • On-site

IPolarity LLC
Recruiting and Staffing Services • 1 - 10 employees
Learn more about IPolarity LLCexternal

$45 - $55/hr

Full-time

Posted 6 days ago

Job description

Machine Learning Engineer – GCP / Vertex AI / Dataproc / Apache Iceberg
Location: Charlotte, NC.
No OPT/CPT
???? Key Responsibilities
• Deploy and manage ML models using Google Vertex AI.
• Build automated ML pipelines for batch and near real-time scoring.
• Develop scalable data processing pipelines using Dataproc, Apache Spark, PySpark, and Spark SQL.
• Design and optimize large-scale data lakes using Apache Iceberg.
• Implement partitioning, schema evolution, versioning, and time-travel capabilities.
• Build data ingestion, transformation, and feature engineering workflows.
• Implement MLOps, CI/CD, model monitoring, retraining, and automation.
• Work with BigQuery and Google Cloud Storage (GCS).
• Monitor model performance, pipeline health, logging, metrics, and alerts.
• Optimize GCP compute resources and cloud costs.
• Support production incidents, reliability, security, and governance.
???? Required Skills
✅ 7+ years of experience in Machine Learning Engineering, Data Engineering, or related areas.
✅ Strong GCP experience.
✅ Hands-on Vertex AI experience.
✅ Dataproc.
✅ Apache Spark / PySpark / Spark SQL.
✅ Apache Iceberg.
✅ Python and SQL.
✅ BigQuery and GCS.
✅ Experience building distributed data and ML pipelines.
✅ Strong understanding of MLOps and ML model lifecycle management.
✅ CI/CD and DevOps experience.
???? Preferred Skills.
⭐ Vertex AI Pipelines / Kubeflow Pipelines.
⭐ Docker / Kubernetes.
⭐ Feature Stores.
⭐ Model Monitoring.
⭐ Terraform / Infrastructure as Code.
⭐ Data Governance / Metadata / Data Lineage.
⭐ Financial Services, AML, Fraud, Risk Analytics, or regulated environments.
???? Ideal Candidate
We are looking for a platform-oriented Machine Learning Engineer who can bridge the gap between Data Science and Data Engineering and transform ML models into scalable, governed, production-ready solutions on GCP.
If you have strong experience with GCP + Vertex AI + Dataproc/PySpark + Apache Iceberg + MLOps, we'd love to connect!