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Google Cloud Machine Learning Engineer Jobs in Miami, FL

Opendoor

Machine Learning Engineer

Miami, FL · On-site

About Opendoor At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth, stability, and community. It ...

Opendoor

Machine Learning Engineer

Miami, FL · On-site

$150 - $230/hr

About the Role -- Senior and Above You're interviewing for Opendoor's ML team which seeks to automate and refine every decision made in our product. We don't slot into silos; you'll build where you ...

Univision

Senior Data Engineer

Miami, FL · On-site

$101K - $137K/yr

Deep expertise in modern cloud-based data platforms, particularly Google Cloud Platform (GCP ... Build and optimize data models and workflows to support analytics, reporting, machine learning, and ...

Univision Communications, Inc.

Senior Data Engineer

Miami, FL · On-site

$101K - $137K/yr

Deep expertise in modern cloud-based data platforms, particularly Google Cloud Platform (GCP ... Build and optimize data models and workflows to support analytics, reporting, machine learning, and ...

Pwc

AI Engineer

Miami, FL · On-site

$55K - $187K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials - Utilizing ...

Acclaim

Principal Machine Learning Engineer

Miami, FL · On-site +1

Strong coding and engineering skills Responsibilities * Develop and improve / Voice Generation models * Train, fine-tune, and evaluate speech models * Bring research ideas into production systems

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Showing results 21-40

All JobsGoogle Cloud Machine Learning Engineer JobsGoogle Cloud Machine Learning Engineer Jobs in Miami, FL

Google Cloud Machine Learning Engineer information

See Miami, FL salary details

$22

$60

$83

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

As of Aug 8, 2026, the average hourly pay for google cloud machine learning engineer in Miami, FL is $60.05, according to ZipRecruiter salary data. Most workers in this role earn between $51.20 and $68.41 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 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 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 are popular job titles related to Google Cloud Machine Learning Engineer jobs in Miami, FL? For Google Cloud Machine Learning Engineer jobs in Miami, FL, the most frequently searched job titles are:
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What cities near Miami, FL are hiring for Google Cloud Machine Learning Engineer jobs? Cities near Miami, FL 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 Miami, FL as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $124,908 per year, or $60.1 per hour.

Sr. Cloud Security Engineer

Stellar IT Solutions LLC

Fort Lauderdale, FL • Hybrid

$70 - $75/hr

Other

Posted 22 days ago

Job description

Title: Sr. Cloud Security Engineer

Location: 5 days onsite Ft. Lauderdale FL area 

Type: 6 month contract to hire

Notes

  • Design, implement, and continuously harden secure landing zones, tenant baselines, and guardrails across Azure, AWS, Google Cloud, and Oracle Cloud Infrastructure — including hybrid and multi-cloud connectivity patterns

  • Develop and maintain cloud security standards, reference patterns, and secure-by-default blueprints that apply consistently across providers, not just one vendor’s stack

  • Lead security reviews and risk assessments for new cloud workloads, migrations, and modernization initiatives, providing actionable remediation guidance to engineering teams

  •  5+ years of experience across cloud engineering, cloud security, and cybersecurity engineering in enterprise environments

  • Genuine multi-cloud expertise: expert-level, hands-on experience in at least one major cloud (Azure, AWS, or Google Cloud) and strong working proficiency across the others, including exposure to Oracle Cloud Infrastructure, with the ability to translate security concepts fluently between providers rather than defaulting to a single vendor’s toolset

  • Cloud identity depth across providers: hands-on experience with Microsoft Entra ID, AWS IAM / Identity Center, Google Cloud IAM, and/or OCI IAM federation, MFA, conditional and context-aware access, privileged access, and workload/non-human identity

  • Practical experience applying AI/ML or large language models to cloud data analysis, detection, triage, or automation

  • Experience designing and securing cloud architectures, hybrid environments, and cloud networking, VNets, VPCs, VCNs, VPNs, private connectivity, firewalls, and zero-trust patterns, on more than one platform

  • Translate cloud security requirements and architecture into deployed, automated controls that operate reliably across heterogeneous platforms, without creating friction for engineering teams

  • Operate as a hands-on engineer who personally builds, configures, tests, and ships high-quality guardrails, automation, and integrations, measuring success in problems solved, not tickets closed

  • Tools: Microsoft Purview, SaaS security posture management, Zscaler (CASB/DLP), Trellix Helix, Cribl, Torq, Rapid7, Terraform, Bicep, CloudFormation, OPA, CI/CD security (GitHub Actions, Azure DevOps),Python, PowerShell, Terraform HCL, Bash and more