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Google Cloud Machine Learning Engineer Jobs in Massachusetts

Jobtailor

Google Cloud Platform Engineer

Lincoln, MA · On-site

$110 - $160/hr

Knowledge and expertise in engineering, operating and maintaining Google Cloud products * Deep knowledge of digital and web service solutions leveraging open-source tools, cloud technologies, and ...

Xometry

Staff Machine Learning Engineer

Waltham, MA

Build for scale - Develop cloud-based production systems powering real-time endpoints and MLOps ... machine learning engineering, with a track record of owning and delivering complex ML systems in ...

Xometry

Staff Machine Learning Engineer

Waltham, MA · On-site

Build for scale - Develop cloud-based production systems powering real-time endpoints and MLOps ... machine learning engineering, with a track record of owning and delivering complex ML systems in ...

STR

Machine Learning Engineer

Woburn, MA · On-site

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML ... cloud, on-prem, desktop, mobile, and edge devices. In addition, you will collaborate closely with ...

Socket.dev

Machine Learning Engineer

Woburn, MA · On-site

$115 - $140/hr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML ... cloud, on-prem, desktop, mobile, and edge devices. In addition, you will collaborate closely with ...

STR

Machine Learning Engineer

Woburn, MA · On-site

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML ... cloud, on-prem, desktop, mobile, and edge devices. In addition, you will collaborate closely with ...

STR

Machine Learning Engineer

Boston, MA

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML ... cloud, on-prem, desktop, mobile, and edge devices. In addition, you will collaborate closely with ...

STR

Machine Learning Engineer

Woburn, MA · On-site

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML ... cloud, on-prem, desktop, mobile, and edge devices. In addition, you will collaborate closely with ...

OneStudyTeam

Senior Machine Learning Engineer

Boston, MA · Remote

$140K - $190K/yr

Our cloud-based platform, StudyTeam, brings research site workflows online and enables sites ... By joining our team as a Senior Machine Learning Engineer , you will play a pivotal role in ...

S&P Global

Machine Learning Engineer II

Cambridge, MA · On-site

We are seeking a mid-level Machine Learning Engineer to help develop and scale RAG systems across the company. This is a hands-on, full-lifecycle ML role with a strong emphasis on retrieval models ...

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All JobsGoogle Cloud Machine Learning Engineer JobsGoogle Cloud Machine Learning Engineer Jobs in Massachusetts

Google Cloud Machine Learning Engineer information

See Massachusetts salary details

$25

$68

$95

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

As of Aug 24, 2026, the average hourly pay for google cloud machine learning engineer in Massachusetts is $68.68, according to ZipRecruiter salary data. Most workers in this role earn between $58.56 and $78.22 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 Massachusetts?

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

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

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

What cities in Massachusetts are hiring for Google Cloud Machine Learning Engineer jobs?

Cities in Massachusetts 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 Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $142,852 per year, or $68.7 per hour.

Google Cloud Platform Engineer

Jobtailor

Lincoln, MA • On-site

$110 - $160/hr

Other

Posted 5 days ago

Job description

  • Plan, engineer, and optimize cloud infrastructure and applications
  • Implement and design cloud-related hardware and software solutions
  • Monitor and analyze system performance across cloud environments
  • Apply standard concepts and practices of SaaS, PaaS, and IaaS models
  • Solve business problems using business process redesign and cloud computing technologies
  • Consult with business process owners and functional leaders to understand needs and recommend solutions
  • Apply business process re-engineering methodologies to support systems modernization
  • Develop documentation for new standard operating procedures and cloud products
  • Prepare and deliver reports, recommendations, operating models, and workflow designs
  • Create methodologies to measure process performance against established metrics
  • Maintain proficiency in Business Process Re-engineering best practices
  • Analyze digital and web service solutions using open-source and cloud technologies
  • Rationalize complex technical information and validate data sources
  • Assess strategic alignment, cost/benefit, and risk for proposed technical solutions
  • Collaborate with Product Managers to define product approaches that meet user needs
  • Support budgeting and resource requirement assessments as needed
  • Recommend actions based on analysis to support organizational decision-making
  • Provide solutions to technical problems of moderate scope under general supervision
  • Provide technical support to operational strategies aligned within your program and initiatives that optimize processes, enhance productivity, and ensure quality across all program functions
  • Ensure 100% of planned hours are worked and recorded
  • Identify and forward to your leadership any opportunities that could lead to growth within your work area
  • Participate in growth efforts as requested
  • Ensure all contractual deliverables are met/exceeded to the customer's satisfaction
  • Complete personal PDP and attend all company meetings (with camera on)
  • Within your program, build productive and positive professional relationships with clients
  • Execute all contract requirements as assigned in accordance with the contract-specific LCAT and requirements
  • Perform other related duties as assigned
Requirements
  • Bachelor’s degree in Information Technology or related field with 4+ years of experience
  • Knowledge and expertise in engineering, operating and maintaining Google Cloud products
  • Deep knowledge of digital and web service solutions leveraging open-source tools, cloud technologies, and agile methodologies
  • Experience applying technical standards, principles, and industry best practices
  • Ability to rationalize complex technical information for diverse audiences
  • Strong analytical skills to interrogate data, validate information, and identify inconsistencies
  • Ability to assess strategic alignment, cost/benefit, and risk for technical solution proposals
  • Demonstrated experience providing solutions to technical problems of moderate complexity
  • Ability to collaborate effectively with cross-functional teams and product managers
  • Current DoD 8570 / 8140 IAT Level II certification
  • One or more cloud certifications (AWS, Azure, Google Cloud, or equivalent) required
Core Competencies

Demonstrates expertise in cloud infrastructure engineering and optimization, with a strong focus on Google Cloud products and business process re-engineering methodologies. Capable of analyzing system performance and providing data-driven solutions to enhance operational efficiency and meet organizational goals.

Highest-signal resume keywords
  • Google Cloud Expertise
  • Business Process Re-engineering
  • Cloud Certifications (AWS, Azure, Google Cloud)
  • Analytical Skills
  • Cross-functional Collaboration
ATS Optimization KeywordsHard Skills
  • Cloud Infrastructure Engineering
  • SaaS, PaaS, IaaS Models
  • Open-source Tools
  • Agile Methodologies
  • Technical Standards and Principles
  • System Performance Analysis
  • Documentation Development
  • Workflow Design
  • Process Performance Measurement
  • Technical Problem Solving
Soft Skills
  • Effective Communication
  • Relationship Building
  • Analytical Thinking
  • Collaboration
  • Decision Making
Certifications & Qualifications
  • DoD 8570 / 8140 IAT Level II Certification
  • Cloud Certifications (AWS, Azure, Google Cloud)
Industry Keywords
  • Cloud Technologies
  • Digital Solutions
  • Web Services
  • Business Process Redesign
  • Cost/Benefit Analysis
  • Risk Assessment
  • Operational Strategies
  • Contractual Deliverables
  • Strategic Alignment
  • Performance Metrics
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