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Remote Ai Infrastructure Engineer Jobs in Wisconsin

EnsoData

Backend Software Engineer

Madison, WI · On-site +1

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 ...

EnsoData

Staff Engineer - Full Stack

Madison, WI · On-site +1

... infrastructure to customer-facing application interfaces. The person in this role will design ... Using AI and machine learning, our software analyzes billions of data points collected from sensors ...

Zendesk

Senior Counsel, Product (AI)

Madison, WI · On-site +1

$140K - $190K/yr

Outstanding candidates will be considered outside of office locations for a fully remote role. Join ... A track record of building trust with product and engineering teams by combining legal expertise ...

Zendesk

Senior Counsel, Product (AI)

Madison, WI · On-site +1

$140K - $190K/yr

Outstanding candidates will be considered outside of office locations for a fully remote role. Join ... A track record of building trust with product and engineering teams by combining legal expertise ...

Wisconsin

AI Technical Lead

Madison, WI · On-site +1

$115K - $140K/yr

Remote work requires successful candidates to possess their own high-speed internet and phone to ... DoIT provides core IT infrastructure services to the university, develops and implements services ...

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Remote Ai Infrastructure Engineer information

What are the key skills and qualifications needed to thrive as a remote AI infrastructure engineer?

To thrive as a Remote AI Infrastructure Engineer, you need expertise in cloud computing, distributed systems, and software engineering, often supported by a degree in computer science or a related field. Familiarity with tools like Kubernetes, Docker, Terraform, and cloud platforms such as AWS, Azure, or GCP is typically required, along with knowledge of CI/CD pipelines and AI/ML frameworks. Strong problem-solving skills, self-motivation, and effective remote communication are essential soft skills for success in this role. These skills ensure robust, scalable AI infrastructure that supports rapid innovation and seamless collaboration across distributed teams.

What is a remote AI infrastructure engineer?

A Remote AI Infrastructure Engineer is a professional who designs, builds, and maintains the systems and tools necessary to support artificial intelligence (AI) projects, all while working remotely. Their responsibilities often include developing and optimizing cloud or on-premise infrastructure, ensuring scalability, managing data pipelines, and supporting machine learning workflows. They work closely with data scientists and software engineers to ensure AI models can be efficiently trained, deployed, and monitored in production environments. The remote aspect allows them to perform these tasks from anywhere, using collaboration tools and cloud platforms.

What are some common challenges faced by remote AI infrastructure engineers, and how can they be addressed?

Remote AI Infrastructure Engineers often encounter challenges such as managing distributed systems, ensuring robust data pipelines, and maintaining high system reliability across different time zones. Collaboration with cross-functional teams can require clear communication and effective use of remote tools. To address these challenges, it's important to establish strong documentation practices, schedule regular check-ins, and utilize automated monitoring and deployment solutions. Staying proactive and adaptable helps ensure seamless infrastructure performance and team alignment.
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Remote Ai Infrastructure Engineer jobs near you

AI Training Specialist - Life Sciences

micro1 AI

Green Bay, WI • Remote

$90 - $120/hr

Part-time

Posted 12 days ago

Job description

Role Title: Bioinformatics Scientist


Role Type: Contractor


Location: Remote


micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze complex datasets related to medicinal chemistry using advanced bioinformatics methodologies.
  2. Provide detailed scientific input and content to support the development and training of AI models.
  3. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis.
  4. Evaluate and synthesize findings from biological, chemical, and clinical data sources.
  5. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry.
  6. Assess AI-generated outputs for scientific accuracy, relevance, and reliability.
  7. Deliver comprehensive written feedback and actionable recommendations for model improvement.


Preferred Qualifications

  1. Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline.
  2. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles.
  3. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.
  4. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME).
  5. Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts.
  6. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science.
  7. Experience collaborating in multidisciplinary or remote project environments is advantageous.

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