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Remote Google Machine Learning Engineer Jobs in Wisconsin

$52 - $71.25/hr

Deploy new machines as required to meet demand. Automate where possible. * Manage SSL certificates ... Experience with Google Kubernetes Engine (GKE) * Experience with Greenplum databases * Experience ...

Using AI and machine learning, our software analyzes billions of data points collected from sensors ... Remote and flexible schedule - we are a remote company with hybrid options and support for flexible ...

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 ...

$171K - $210K/yr

Data Engineering, Data Science or Machine Learning * Operations, Security and Data Governance ... Employee Resource Groups EEO/VEVRAA #LI-MH2 #LI-Remote

Cloud Engineer II

Neenah, WI · Remote

$57.50 - $76.75/hr

... as Google Cloud and AWS. This position focuses on supporting the Cloud environment as well as ... Machines, Microsoft's PaaS solutions, and SaaS solutions. About Jewelers Mutual Jewelers Mutual ...

The position supports advanced analytics, machine learning, and federated research capabilities ... Working closely with data engineers, AI specialists, securityanalyst, and governance leaders, the ...

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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 the most commonly searched types of Google Machine Learning Engineer jobs in Wisconsin? The most popular types of Google Machine Learning Engineer jobs in Wisconsin are:
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:
Cloud Platform Engineer (GCP) - Remote

Cloud Platform Engineer (GCP) - Remote

micro1 AI

Milwaukee, WI • Remote

$20 - $300/hr

Part-time

Medical, Retirement, PTO

Posted 3 days ago

New


Job description

GCP DevOps Engineer


Job Type: Full-time


Location: Remote - US


Job Summary:

Join our team as a GCP DevOps Engineer and play a crucial role in designing, building, and maintaining modern cloud infrastructure solutions. You will collaborate closely with talented engineers and stakeholders to deliver scalable, reliable, and secure environments on Google Cloud Platform (GCP). We are seeking a proactive professional with a passion for infrastructure automation and a strong commitment to clear, effective communication.


Key Responsibilities:

• Design, implement, and manage scalable cloud infrastructure solutions on GCP.

• Automate deployment, monitoring, and management processes using industry-leading DevOps practices.

• Administer and optimize Kubernetes clusters for maximum reliability and performance.

• Collaborate with development teams to streamline CI/CD pipelines and refine workflows.

• Ensure the security and compliance of cloud environments by applying best practices.

• Proactively identify and resolve infrastructure bottlenecks and incidents.

• Document solutions and processes with a focus on clarity and thoroughness to support team knowledge sharing.


Required Skills and Qualifications:

• Strong hands-on experience with Google Cloud Platform (GCP).

• Deep expertise in implementing and operating cloud infrastructure in production settings.

• Proficiency with Kubernetes administration and orchestration.

• Solid understanding of DevOps methodologies, tools, and best practices.

• Experience building and maintaining CI/CD pipelines.

• Competence with infrastructure-as-code tools (e.g., Terraform, Deployment Manager).

• Excellent written and verbal communication skills; ability to convey complex concepts clearly.


Preferred Qualifications:

• GCP certifications such as Associate Cloud Engineer or Professional DevOps Engineer.

• Experience with hybrid or multi-cloud environments.

• Familiarity with security best practices and compliance standards relevant to cloud-native architectures.


Compensation & Benefits Notice


The national pay range for this full-time position is base salary of $160,000-$220,000. All employees are eligible for equity compensation, and employees may also receive performance-based bonuses, dependent on role and subject to company policies. micro1 provides a comprehensive benefits package, including up to 100% reimbursement for health-insurance premiums, paid time off, a 401(K) plan with a company match, and additional benefits designed to support a high-performing, remote-first workforce.


micro1 is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation during the application process, reach out to support@micro1.ai.


Our hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making.


Disclaimer


The information contained in this job posting, including but not limited to role responsibilities, qualifications, compensation, and benefits, is provided for informational purposes only and does not constitute a binding offer of employment. micro1 reserves the right to amend, modify, or withdraw any portion of this posting at its sole discretion and without prior notice. All employment decisions are made in accordance with applicable laws and regulations.