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Remote Machine Learning Jobs in Madison, WI (NOW HIRING)

The position automates environments for advanced analytics, machine learning, and federated ... It is anticipated that this position will be remote and requires work be performed at an offsite ...

The position supports advanced analytics, machine learning, and federated research capabilities ... It is anticipated that this position will be remote and requires work be performed at an offsite ...

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

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 ...

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Remote Machine Learning information

See Madison, WI salary details

$25.7K

$42.9K

$88.7K

How much do remote machine learning jobs pay per year?

As of Jul 13, 2026, the average yearly pay for remote machine learning in Madison, WI is $42,908.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,700.00 and $46,400.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in high-demand markets.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

How to make 2000 a week working from home?

Remote machine learning professionals can earn $2,000 or more weekly by taking on high-paying freelance projects, consulting roles, or working for companies that offer remote positions with competitive salaries. Building specialized skills in programming, data analysis, and tools like Python, TensorFlow, or cloud platforms can increase earning potential. Consistent work, a strong portfolio, and networking are key to reaching this income level from home.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Are there remote machine learning jobs?

Yes, remote machine learning jobs are widely available across various industries, often requiring skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch. Many companies offer flexible schedules and remote work options for qualified candidates, especially in tech and research sectors.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and model optimization. While AI automation tools can handle certain tasks, MLEs are essential for creating, fine-tuning, and maintaining complex AI systems, making complete replacement unlikely in the near term.
What are the most commonly searched types of Machine Learning jobs in Madison, WI? The most popular types of Machine Learning jobs in Madison, WI are:
What are popular job titles related to Remote Machine Learning jobs in Madison, WI? For Remote Machine Learning jobs in Madison, WI, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning jobs in Madison, WI look for? The top searched job categories for Remote Machine Learning jobs in Madison, WI are:
What cities near Madison, WI are hiring for Remote Machine Learning jobs? Cities near Madison, WI with the most Remote Machine Learning job openings:
Infographic showing various Remote Machine Learning job openings in Madison, WI as of July 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $42,908 per year, or $20.6 per hour.
Cloud Infrastructure Architect

Cloud Infrastructure Architect

University of Wisconsin-Madison

Madison, WI • On-site, Remote

Full-time

Retirement, PTO

Posted 11 days ago


University Of Wisconsin-Madison rating

8.3

Company rating: 8.3 out of 10

Based on 56 frontline employees who took The Breakroom Quiz

105th of 553 rated colleges and universities


Job description

Current Employees: If you are currently employed at any of the Universities of Wisconsin, log in to Workday to apply through the internal application process.
Job Category:
Academic Staff
Employment Type:
Regular
Job Profile:
DevOps Engineer III
Job Summary:
The Wisconsin Health Data Hub (WHDH), funded by the U.S. Economic Development Administration (EDA), is developing a secure, cloud-native data platform designed to deliver high-quality real-world data to support biomedical research, advanced analytics, and AI-driven discovery.
The Cloud Infrastructure Architect provides technical leadership responsible for designing, implementing, and automating the infrastructure, deployment pipelines, and operational environment of WHDH's data platform. This role ensures the secure, scalable, and highly available integration of infrastructure components supporting complex clinical and research data assets across a cloud-based environment. The position automates environments for advanced analytics, machine learning, and federated research capabilities while strictly maintaining compliance with HIPAA and institutional data security standards.
Working closely with data solutions architects, data engineers, AI specialists, and security leaders, the Cloud Infrastructure Architect will translate architectural and operational requirements into scalable Infrastructure as Code (IaC) solutions and robust CI/CD practices that support WHDH's long-term platform strategy.
Key Responsibilities
Cloud Infrastructure and Platform Orchestration
Design and implement the scalable, secure, cloud-native infrastructure framework supporting WHDH's data platform using Infrastructure as Code (IaC) principles (e.g., Terraform, CloudFormation).
Develop and maintain automated, elastic environments capable of ingesting, harmonizing, storing, and delivering massive structured and unstructured health datasets.
Optimize containerized environments and orchestration layers (e.g., Kubernetes, ECS) to seamlessly support complex research workflows and distributed computing.
Architect high-performance computing environments and automated provisioning pipelines tailored for AI, machine learning, and large-scale data analysis.
Deployment Pipelines and Continuous Integration (CI/CD)
Build and manage secure, automated CI/CD pipelines for data engineering workflows, application code, and infrastructure deployments.
Enable reliable, continuous deployment methodologies that ensure zero-downtime updates and seamless system testing across health systems and research institutions.
Implement operational monitoring, logging, and alerting systems (e.g., Prometheus, Grafana, ELK stack) to proactively ensure platform reliability, uptime, and performance.
DevSecOps and Compliance Automation
Bake strict security controls into the automated provisioning process, ensuring end-to-end alignment with HIPAA, institutional policies, and research data security standards.
Establish best practices for DevSecOps, including automated vulnerability scanning, secret management, and compliance-as-code.
Design and maintain immutable infrastructure patterns that enforce granular access control, precise audit logging, and strict data governance across the WHDH ecosystem.
It is anticipated that this position will be remote and requires work be performed at an offsite, non-campus work location. The selected candidate must reside within the State of Wisconsin or move to the State within a reasonable time frame from the start date of the position.
Key Job Responsibilities:
  • Architects and manages containerized and distributed computing platforms that enable advanced analytics, machine learning, AI-driven research workloads, and high-performance data processing in secure cloud environments.
  • Collaborates with engineers, data scientists, architects, and research stakeholders to deliver scalable platform solutions that enable authorized users to securely access, process, and analyze distributed biomedical datasets.
  • Builds and optimizes observability frameworks, including monitoring, logging, alerting, and performance management solutions, to ensure system health, resiliency, and rapid incident response.
  • Manages, maintains, selects, and develops automation tools and infrastructure, including security configurations
  • Performs integration, migration, configuration, and security of existing applications and services into automated infrastructures
  • Serves as a subject matter expert to internal stakeholders, providing guidance and training to staff
  • Designs and implements platform capabilities that support secure data sharing, federated access, identity and access management, and privacy-preserving workflows while maintaining rigorous security and governance controls.
  • Serves as technical lead for one or more aspects of the system
  • Develops, programs, and/or deploys automation workflows for deployment, configuration, and/or monitoring of systems/services
  • Analyzes requirements and communicates and coordinates with staff and internal stakeholders related to the system and/or project

Department:
School of Medicine and Public Health, Office of Informatics, Wisconsin Health Data Hub.
The Wisconsin Health Data Hub (WHDH) is a grant-funded initiative within the Information and Information Technology (IIT) Division at the University of Wisconsin-Madison School of Medicine and Public Health. WHDH brings together a multidisciplinary team of technologists responsible for designing, implementing, and operating a secure data enclave that supports the responsible use of real-world health data for biomedical research.
The WHDH team develops and manages a scalable data platform that enables researchers to efficiently access, integrate, and analyze large-scale health datasets from participating health systems. By providing advanced data services, governance frameworks, and analytical capabilities, WHDH accelerates the research lifecycle-from project conception and data acquisition to analysis and discovery-while ensuring compliance with applicable regulatory, privacy, and security requirements.
Compensation:
The starting salary for the position is $115,000 annually; but is negotiable based on experience and qualifications.
Employees in this position can expect to receive benefits such as generous vacation, holidays, and sick leave; competitive insurances and savings accounts; retirement benefits. For more information, refer to the campus benefits webpage.
SMPH Faculty /Academic Staff Benefits Flyer 2026
Required Qualifications:
  • 8 years of experience designing, implementing, and maintaining enterprise-scale cloud infrastructure and automated environments.

  • Expertise with cloud-native platform orchestration (e.g., AWS, Azure, GCP) and managing infrastructure for distributed data solutions or containerized environments (e.g., Kubernetes, Docker).

  • Experience designing secure CI/CD deployment pipelines, automation workflows, and robust infrastructure integration frameworks.

  • Familiarity with healthcare or biomedical research data environments and relevant regulatory security compliance (e.g., HIPAA).

Preferred Qualifications:
  • Experience implementing DevSecOps practices, cloud-native security controls, and compliance-as-code within regulated healthcare data standards or interoperability frameworks.

  • Experience building and optimizing infrastructure to support AI/ML pipelines, MLOps, and advanced analytics workloads.

  • Expertise with securing and automating infrastructure for federated data platforms and multi-institutional data collaborations.

  • Experience working in federally funded research programs or academic research environments.

  • Strong documentation skills (e.g., creating architecture diagrams, runbooks) and proven technical leadership skills.

Education:
Bachelor's degree preferred; focus in Computer Science, Information Systems, Software Engineering, or a related technical field preferred
How to Apply:
For the best experience completing your application, we recommend using Chrome or Firefox as your web browser.
To apply for this position, select either "I am a current employee" or "I am not a current employee" under Apply Now. You will then be prompted to upload your application materials.
Important: The application has only one attachment field. Upload the following documents in that field, either as a single combined file or as multiple files in the same upload area.
• Cover letter (required)
• Resume (required)
Your cover letter should address how your training and experience aligns with the required and preferred qualifications listed above. Application reviewers will rely on these written materials to determine which applicants move forward in the process. References will be requested from final candidates. All applicants will be notified once the search concludes and a candidate is selected.
University sponsorship is not available for this position, including transfers of sponsorship and TN visas. The selected applicant will be responsible for ensuring their continuous eligibility to work in the United States (i.e. a citizen or national of the United States, a lawful permanent resident, a foreign national authorized to work in the United States without the need of an employer sponsorship) on or before the effective date of appointment. This position is an ongoing position that will require continuous work eligibility. If you are selected for this position you must provide proof of work authorization and eligibility to work.
Contact Information:
Cody Roekle, croekle@wisc.edu, 16082637676
Relay Access (WTRS): 7-1-1. See RELAY_SERVICE for further information.
Institutional Statement on Diversity:
Diversity is a source of strength, creativity, and innovation for UW-Madison. We value the contributions of each person and respect the profound ways their identity, culture, background, experience, status, abilities, and opinion enrich the university community. We commit ourselves to the pursuit of excellence in teaching, research, outreach, and diversity as inextricably linked goals.
The University of Wisconsin-Madison fulfills its public mission by creating a welcoming and inclusive community for people from every background - people who as students, faculty, and staff serve Wisconsin and the world.
The University of Wisconsin-Madison is an Equal Opportunity Employer.
Qualified applicants will receive consideration for employment without regard to, including but not limited to, race, color, religion, sex, sexual orientation, national origin, age, pregnancy, disability, or status as a protected veteran and other bases as defined by federal regulations and UW System policies. We promote excellence by acknowledging skills and expertise from all backgrounds and encourage all qualified individuals to apply. For more information regarding applicant and employee rights and to view federal and state required postings, visit the Human Resources Workplace Poster website.
To request a disability or pregnancy-related accommodation for any step in the hiring process (e.g., application, interview, pre-employment testing, etc.), please contact the Divisional Disability Representative (DDR) in the division you are applying to. Please make your request as soon as possible to help the university respond most effectively to you.
Employment may require a criminal background check. It may also require your references to answer questions regarding misconduct, including sexual violence and sexual harassment.
The University of Wisconsin System will not reveal the identities of applicants who request confidentiality in writing, except that the identity of the successful candidate will be released. See Wis. Stat. sec. 19.36(7).
The Annual Security and Fire Safety Report contains current campus safety and disciplinary policies, crime statistics for the previous 3 calendar years, and on-campus student housing fire safety policies and fire statistics for the previous 3 calendar years. UW-Madison will provide a paper copy upon request; please contact the University of Wisconsin Police Department.

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University of Wisconsin logo

About University of Wisconsin

Sourced by ZipRecruiter

The University of Wisconsin, based in Madison, WI, US, functions in the educational industry and is a renowned and respected institution for higher education. Its official website is wisc.edu. Established in 1848, this public research university is recognized globally for its innovative approach to education, research, creativity, and public service. It embodies a strong commitment to academic freedom and academic excellence. As a major contributor to the Wisconsin Idea, it aims to accomplish its mission of generating well-rounded individuals who will contribute substantially to society, the local community, and the global economy.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Madison, WI, US

Year founded

2005