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Google Cloud Machine Learning Engineer Jobs in Houston, TX

Dow

Machine Learning Engineer

Houston, TX · On-site

As a Machine Learning Engineer in our Data & Analytics Platforms team specializing in data and ... Cloud Computing: Designing and operating cloud-native architectures on Azure (e.g., Databricks ...

Dow

Machine Learning Engineer

Houston, TX · On-site

$120 - $160/hr

As a Machine Learning Engineer in our Data & Analytics Platforms team specializing in data and ... Cloud Computing: Designing and operating cloud-native architectures on Azure (e.g., Databricks ...

Deloitte

Cyber - Google Cloud Security - Manager

Houston, TX · On-site

$106K - $143K/yr

... machine learning security, container security, data protection, monitoring, and secure delivery ... Serving as the primary day-to-day client contact, driving outcomes across engineering, security ...

Socket.dev

Robotics Machine Learning Engineer

Houston, TX · On-site

$120 - $180/hr

We're looking for a Machine Learning Engineer to drive our machine learning strategy. We are ... Experience with cloud computing to develop models, store data, etc. (AWS, Azure, GCP) * Strong ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow ... Experience with cloud platforms (AWS preferred) and modern MLOps practices: containerization ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow ... Experience with cloud platforms (AWS preferred) and modern MLOps practices: containerization ...

Vitol

Senior Machine Learning Engineer

Houston, TX

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow ... Experience with cloud platforms (AWS preferred) and modern MLOps practices: containerization ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$116K - $154K/yr

They are seeking an experienced Machine Learning Engineer to join their data science and machine ... ARIMA, cointegration, regime-switching models) • Data orchestrators (Airflow, Dagster) and cloud ...

Bespoke Labs

Machine Learning Engineer

Houston, TX · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

Accenture

Google Senior Data Engineer

Houston, TX · On-site

$94K - $266K/yr

You Are A hands-on Engineer with foundational experience in Data Engineering, Analytics, or Machine Learning-now building deep expertise in Google Cloud Platform (GCP). You are eager to apply ...

New

Beth Page tech

Senior Machine Learning Engineer

Houston, TX · On-site

$99K - $137K/yr

Senior Machine Learning Engineer Location: Houston, TX Environment: Standard, 5-days onsite : Must ... Cloud (AWS) and containerization (Docker) experience. Nice-to-Have (Preferred Experience)

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

As of Aug 14, 2026, the average hourly pay for google cloud machine learning engineer in Houston, TX 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 the most commonly searched types of Google Cloud Machine Learning Engineer jobs in Houston, TX?

The most popular types of Google Cloud Machine Learning Engineer jobs in Houston, TX are:

What are popular job titles related to Google Cloud Machine Learning Engineer jobs in Houston, TX?

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

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

The top searched job categories for Google Cloud Machine Learning Engineer jobs in Houston, TX are:

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Cities near Houston, TX 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 Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 18% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $124,913 per year, or $60.1 per hour.

Machine Learning Engineer

Dow

Houston, TX • On-site

Full-time

Medical, Life, Retirement, PTO

Posted 15 days ago

Dow rating

8.6

Company rating: 8.6 out of 10

Based on 89 frontline employees who took The Breakroom Quiz

16th of 100 rated chemical manufacturers

Job description

At Dow, we believe in putting people first and we're passionate about delivering integrity, respect and safety to our customers, our employees and the planet.
Our people are at the heart of our solutions. They reflect the communities we live in and the world where we do business. Their diversity is our strength. We're a community of relentless problem solvers that offers the daily opportunity to contribute with your perspective, transform industries and shape the future. Our purpose is simple - to deliver a sustainable future for the world through science and collaboration. If you're looking for a challenge and meaningful role, you're in the right place.
About you and this role
Dow has an exciting and challenging opportunity for a Machine Learning Engineer within our Enterprise Data & Analytics organization located in Houston, TX; Midland, MI; or Champaign, IL.
As a Machine Learning Engineer in our Data & Analytics Platforms team specializing in data and analytics solutions, you will work with a cross-functional team whose objective is to deliver solutions that drive business value for Dow. In this role, you will work closely with data engineers, data scientists, domain experts, and software engineers to design, develop, and deploy machine learning systems, including training and inference pipelines on the Azure Databricks platform. You will also help drive a culture around setting standards and adopting best practices for machine learning and MLOps across the organization.
Responsibilities
  • Designs and implements pipelines and other workflow infrastructure to meet the requirements for new AI/ML solutions that involve online, batch, or real-time inference
  • Deploys and monitors machine learning models in production using Databricks Model Registry, Jobs, and Workspace
  • Frequently collaborates with data engineers, DevOps/platform engineers, data scientists, and domain experts as part of a comprehensive MLOps framework to ensure AI/ML solutions are performant, reliable, and maintainable
  • Works frequently with application development teams to ensure seamless integrations
  • Works proficiently with various ML frameworks, such as scikit-learn, TensorFlow, PyTorch, Keras, as well as distributed frameworks like Spark MLlib and Ray
  • Performs data analysis, feature engineering, model selection, hyperparameter optimization, and model evaluation using Databricks MLFlow, Delta Lake, and SQL Analytics and other tools as part of the end-to-end ML lifecycle
  • Researches and implements new machine learning techniques and methods using Databricks, staying abreast of the latest trends and technologies
  • Documents and communicates machine learning results and insights to stakeholders using Databricks notebooks and dashboards
  • Understands IT security policies and implements them as part of new solution designs
  • Follows and promotes the best practices and standards for machine learning and MLOps across the organization using Databricks and Azure DevOps

Your Skills
  • Solutions Delivery: End-to-end ownership of Azure data solutions-translating ambiguous business needs into robust architectural blueprints, then delivering through design, build, test, deployment, and post-launch monitoring with a focus on reliability, performance, and cost efficiency.
  • Cloud Computing: Designing and operating cloud-native architectures on Azure (e.g., Databricks Lakehouse, ADF/Workflows, Functions, Logic Apps, Azure SQL) with CI/CD and IaC to scale securely and economically for ML, BI, streaming, and web applications.
  • Integration Services: Building secure, high-throughput integrations-REST APIs and event/stream pipelines (e.g., Event Hubs/Kafka)-to connect polyglot data stores (SQL Server, Cosmos DB, Neo4j) and enable real-time and batch data products.
  • Security Awareness: Embedding governance, identity, and compliance into the architecture (OAuth/RBAC, data governance, re-authorization/ownership verification), enforcing code reviews and automated controls across pipelines and deployments.
  • Strategic Planning: Aligning platform roadmaps and technology choices with enterprise strategy, mentoring engineers on best practices, defining standards and KPIs, and prioritizing modernization and cost-optimization initiatives that maximize business impact.

Qualifications
  • A minimum of a Bachelor's degree, or 8 years relevant experience, or relevant military experience at an E6 rank/Petty Officer 2nd Class or higher is required
  • A minimum of 3 years of experience developing solutions in machine learning, data science, or related field
  • A minimum requirement for this U.S. based position is the ability to work legally in the United States. No visa sponsorship/support is available for this position, including for any type of U.S. permanent residency (green card) process

Preferred qualifications
  • A degree in computer science, engineering, mathematics, statistics, data science or related field
  • Proficient in Python and one or more machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, etc
  • Experience in developing and deploying machine learning models and pipelines on the Databricks platform using Databricks MLflow, Delta Lake, SQL Analytics, Model Registry, Jobs, and Workspace
  • Strong knowledge of machine learning concepts, techniques, and algorithms
  • Ability to perform data analysis, feature engineering, model selection, optimization, and evaluation using Databricks
  • Ability to communicate complex machine learning concepts and results to technical and non-technical audiences using Databricks notebooks and dashboards
  • Ability to work independently and collaboratively in a fast-paced and dynamic environment
  • Curiosity and passion for learning new machine learning skills and technologies using Databricks
  • Strong knowledge of data modeling, data warehousing, and ETL processes
  • Experience designing and deploying into production both traditional and generative AI systems
  • Proficiency in SQL and experience with big data technologies such as Apache Spark and Hive
  • Experience working within Azure Machine Learning
  • Experience containerizing and deploying ML models to Azure Kubernetes Service
  • Experience with Azure Data Factory, Azure Data Lake Storage Gen2, and other Azure services
  • Multi-application and cross-platform design experience
  • Understanding of data lakehouse platform design and associated workflows
  • Ability to thrive in challenging situations and solve complex problems
  • Ability to manage own work effort in multiple projects with little supervision
  • Interested in emerging technologies with the ability to quickly learn and exploit cutting edge offerings to achieve business objectives

Additional notes
  • This position does not offer relocation assistance
  • This position does not have people leadership responsibility. This position is an Independent Contributor; however, you may act as coach and mentor to junior resources

Benefits - What Dow offers you
We invest in you.
Dow invests in total rewards programs to help you manage all aspects of you: your pay, your health, your life, your future, and your career. You bring your background, talent, and perspective to work every day. Dow rewards that commitment by investing in your total wellbeing.
Here are just a few highlights of what you would be offered as a Dow employee:
  • Equitable and market-competitive base pay and bonus opportunity across our global markets, along with locally relevant incentives.
  • Benefits and programs to support your physical, mental, financial, and social well-being, to help you get the care you need...when you need it.
  • Competitive retirement program that may include company-provided benefits, savings opportunities, financial planning, and educational resources to help you achieve your long term financial-goals.
    • Employee stock purchase programs (availability varies depending on location).
  • Student Debt Retirement Savings Match Program (U.S. only).
    • Dow will take the value of monthly student debt payments and apply them as if they are contributions to the Employees' Savings Plan (401(k)), helping employees reach the Company match.
  • Robust medical and life insurance packages that offer a variety of coverage options to meet your individual needs. Travel insurance is also available in certain countries/locations.
  • Opportunities to learn and grow through training and mentoring, work experiences, community involvement and team building.
  • Workplace culture empowering role-based flexibility to maximize personal productivity and balance personal needs.
  • Competitive yearly vacation allowance.
  • Paid time off for new parents (birthing and non-birthing, including adoptive and foster parents).
  • Paid time off to care for family members who are sick or injured.
  • Paid time off to support volunteering and Employee Resource Group's (ERG) participation.
  • Wellbeing Portal for all Dow employees, our one-stop shop to promote wellbeing, empowering employees to take ownership of their entire wellbeing journey.
  • On-site fitness facilities to help stay healthy and active (availability varies depending on location).
  • Employee discounts for online shopping, cinema tickets, gym memberships and more.
  • Additionally, some of our locations might offer:
    • Transportation allowance (availability varies depending on location)
    • Meal subsidiaries/vouchers (availability varies depending on location)
    • Carbon-neutral transportation incentives e.g. bike to work (availability varies depending on location)

Join our team, we can make a difference together.
About Dow
Dow (NYSE: DOW) is one of the world's leading materials science companies, serving customers in high-growth markets such as packaging, infrastructure, mobility and consumer applications. Our global breadth, asset integration and scale, focused innovation, leading business positions and commitment to sustainability enable us to achieve profitable growth and help deliver a sustainable future. We operate manufacturing sites in 30 countries and employ approximately 36,000 people. Dow delivered sales of approximately $43 billion in 2024. References to Dow or the Company mean Dow Inc. and its subsidiaries. Learn more about us and our ambition to be the most innovative, customer-centric, inclusive and sustainable materials science company in the world by visiting www.dow.com.
As part of our dedication to inclusion, Dow is committed to equal opportunities in employment. We encourage every employee to bring their whole self to work each day to not only deliver more value, but also have a more fulfilling career. Further information regarding Dow's equal opportunities is available on www.dow.com.
Dow is an Equal Employment Opportunity employer and is committed to providing opportunities without regard for race, color, religion, sex, including pregnancy, sexual orientation, or gender identity, national origin, age, disability and genetic information, including family medical history. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may call us at 1-833-My Dow HR (833-693-6947) and select option 8.

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