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Remote Google Machine Learning Engineer Jobs in Wisconsin

micro1 AI

Corporate Counsel - Remote

Madison, WI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

micro1 AI

Corporate Counsel - Remote

Green Bay, WI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

micro1 AI

Corporate Counsel - Remote

Milwaukee, WI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

micro1 AI

Law Professor - Remote

Milwaukee, WI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

micro1 AI

Law Professor - Remote

Green Bay, WI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

micro1 AI

Law Professor - Remote

Madison, WI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

micro1 AI

Corporate Counsel - Remote

Kenosha, WI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

micro1 AI

Law Professor - Remote

Kenosha, WI · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Qualysoft

Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote Projektsprache: Deutsch und Englisch Aufgaben: ... Microsoft Foundry, Azure Cognitive Services, Azure Machine Learning Erfahrung in der Entwicklung ...

EnsoData

Implementation Engineer

Madison, WI · On-site +1

$80K - $85K/yr

Using AI and machine learning, our software analyzes billions of data points collected from sensors ... Hybrid/Remote Company - we are a company with hybrid and remote options. That being said, we have ...

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Remote Google Machine Learning Engineer information

What is a Remote Google Machine Learning Engineer?

A Remote Google Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models and artificial intelligence solutions, often using Google Cloud technologies, while working from a remote location. These engineers collaborate with cross-functional teams to solve complex business problems, optimize data pipelines, and improve model performance. Their responsibilities typically include data preprocessing, model selection, training, evaluation, and deployment, all while ensuring scalability and security. Working remotely allows them to contribute to projects from anywhere, leveraging cloud-based tools and collaboration platforms.

What are the key skills and qualifications needed to thrive as a Remote Google Machine Learning Engineer, and why are they important?

To thrive as a Remote Google Machine Learning Engineer, you need a strong background in computer science, mathematics, and machine learning algorithms, typically supported by a relevant degree and experience in building scalable models. Proficiency with tools such as TensorFlow, Python, Google Cloud Platform (GCP), and familiarity with distributed systems is essential. Excellent problem-solving, communication, and self-management skills are crucial for effective remote collaboration and innovation. These capabilities enable engineers to deliver impactful machine learning solutions while seamlessly integrating with global Google teams.

How do Remote Google Machine Learning Engineers typically collaborate with cross-functional teams while working from different locations?

Remote Google Machine Learning Engineers often use a combination of video conferencing, cloud-based collaboration tools, and shared code repositories to work closely with data scientists, product managers, and software engineers. Regular stand-up meetings, sprint planning sessions, and detailed documentation help ensure everyone is aligned and project milestones are met. Despite being remote, engineers are encouraged to proactively communicate progress, share insights, and participate in code reviews to maintain a strong team dynamic and drive successful project outcomes.
What are popular job titles related to Remote Google Machine Learning Engineer jobs in Wisconsin? For Remote Google Machine Learning Engineer jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Remote Google Machine Learning Engineer jobs in Wisconsin look for? The top searched job categories for Remote Google Machine Learning Engineer jobs in Wisconsin are:
What cities in Wisconsin are hiring for Remote Google Machine Learning Engineer jobs? Cities in Wisconsin with the most Remote Google Machine Learning Engineer job openings:
Remote Google Machine Learning Engineer jobs near you

Kubernetes DevOps Engineer (Remote)

Tartan Solutions

Milwaukee, WI • On-site, Remote

$52 - $71.25/hr

Full-time

Posted 13 days ago

Job description

We are looking for an experienced DevOps Engineers interested in building, maintaining, and scaling PlaidCloud on Kubernetes. This position requires a keen eye for detail to ensure consistency in provisioning and high availability of resources.
The position is also responsible for supporting many customer deployments through Kubernetes automation such as use of HPAs and VPAs to ensure good resource usage while maintaining a highly responsive system.
Key responsibilities include:
  • Staging servers and automated provisioning for Kubernetes cluster
  • Utilize ArgoCD ApplicationSets to manage many isolated deployments
  • Monitoring and managing databases and file backups using disk snapshots, Google Cloud Storage, and other approaches
  • Automate restoration of databases and backups
  • Monitoring and managing RabbitMQ in a high availability configuration
  • Managing and monitoring a Greenplum database clusters in a high availability shared nothing configuration
  • Managing and monitoring Redis in a high availability configuration
  • Monitoring server performance and optimizing server selection and cost
  • Deploy new machines as required to meet demand. Automate where possible.
  • Manage SSL certificates, firewalls, load balancers, and other infrastructure through our infrastructure provider
  • Monitor and test system intrusion processes
  • Manage and configure DoS prevention tools
  • Make recommendations and work with software development teams to improve infrastructure usage and simplify design where possible
  • Deploy and improve logging and monitoring metrics to support insight and prioritize engineering changes
  • Improve the use of tracking metrics to better understand usage patterns
  • Work with the software development teams to close testing gaps and support continuous integration processes
  • Ensure a Kubernetes first approach with highly automated processes, best practices, and good resource usage

Ideal Qualifications
  • Strong familiarity with DevOps processes and approaches, especially with GitOps Kubernetes solutions
  • Experience with deployment tools and deployment automation
  • Strong understanding of Linux/Unix configuration processes
  • Strong understanding of security best practices
  • Strong understanding of Jenkins and Github Actions automation pipelines
  • Strong written communications skills

Bonus Qualifications
  • Experience with ArgoCD
  • Experience with Google Kubernetes Engine (GKE)
  • Experience with Greenplum databases
  • Experience with Python
  • Experience with Redis
  • Experience with RabbitMQ
  • Experience with Apache Superset
  • Experience with network and web application security
  • Experience with Git/GitHub automation

Apply