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Google Cloud Machine Learning Engineer Jobs in Louisiana

Workiva

$40/hr

... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ... Knowledge of cloud platforms such as AWS * Proficiency with Python and/or Go * Familiarity with ...

Workiva

$40/hr

... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ... Knowledge of cloud platforms such as AWS * Proficiency with Python and/or Go * Familiarity with ...

New

Workiva

$40/hr

... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ... Knowledge of cloud platforms such as AWS * Proficiency with Python and/or Go * Familiarity with ...

Workiva

$40/hr

... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ... Knowledge of cloud platforms such as AWS * Proficiency with Python and/or Go * Familiarity with ...

Workiva

$40/hr

... Machine Learning Engineer * Help integrate tools such as LlamaIndex and LlamaParse into existing ... Knowledge of cloud platforms such as AWS * Proficiency with Python and/or Go * Familiarity with ...

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Google Cloud Machine Learning Engineer information

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

As of Sep 3, 2026, the average hourly pay for google cloud machine learning engineer in Louisiana is $53.77, according to ZipRecruiter salary data. Most workers in this role earn between $45.82 and $61.25 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.

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

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Google Cloud Machine Learning Engineer jobs near you
Infographic showing various Google Cloud Machine Learning Engineer job openings in Louisiana 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 $111,852 per year, or $53.8 per hour.

Senior Machine Learning Engineer

Bollinger Shipyards

Raceland, LA

$99K - $136K/yr

Full-time

Re-posted 18 days ago

Bollinger Shipyards rating

6.5

Company rating: 6.5 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

Job description

Job Title: Senior Machine Learning Engineer

Location: Mulitple Locations

Position Overview:

The Senior ML Engineer is responsible for operationalizing machine learning and AI solutions into scalable, reliable, and production-ready enterprise systems. This role bridges data science, software engineering, and infrastructure disciplines to deploy, monitor, optimize, and support AI solutions that drive operational and business outcomes.

Key Responsibilities: 

•             Deploy, integrate, and maintain machine learning and AI solutions within enterprise workflows and operational systems

•             Design and develop scalable ML pipelines, feature stores, APIs, and model-serving infrastructure

•             Collaborate with Data Scientists to productionize models and improve deployment readiness

•             Monitor model performance, drift, availability, and reliability across production environments

•             Implement processes for model retraining, versioning, governance, and lifecycle management

•             Partner with Data Engineering teams to support feature engineering and data pipeline integration

•             Ensure ML solutions are secure, scalable, maintainable, and aligned with enterprise architecture standards

•             Support AI applications across forecasting, operational optimization, bidding, scheduling, maintenance, and automation use cases

•             Troubleshoot and resolve issues related to model deployment and operational performance

•             Contribute to ML engineering standards, best practices, and platform improvements

•             Document architecture, deployment processes, and operational support procedures

 

Qualifications: 

·       Bachelor’s degree in Computer Science, Software Engineering, Data Science, or related field

·       6–10 years in ML or software engineering

·       Strong Python and ML deployment experience

·       Experience with cloud ML systems

 

Skills: 

•             Experience with Azure ML, Databricks, ML Ops, or similar cloud AI platforms

•             Experience in manufacturing, industrial, operational, or engineering environments

•             Familiarity with large language models, Generative AI, and intelligent automation

•             Experience supporting enterprise AI applications integrated with ERP or operational systems

•             Knowledge of monitoring, observability, and model governance practices

•             Experience with Docker, Kubernetes, and infrastructure-as-code practices

Bollinger is an equal opportunity employer and is committed to providing employment opportunities to minorities, females, veterans and disabled individuals, and without regard to sexual orientation and gender identity. 

What Bollinger Shipyards employees say

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