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Remote Machine Learning Jobs in Tucson, AZ (NOW HIRING)

SOS International LLC

ML Administrator

Tucson, AZ · Remote

Manage machine learning model versioning, lineage tracking, and compliance with governance policies ... Remote Working at SOSi All interested individuals will receive consideration and will not be ...

Spara Technologies

Sr. Software Engineer (Remote)

Tucson, AZ · Remote

$125.40K - $165.30K/yr

About Spara Technologies Spara Technologies delivers advanced engineering, staffing, and mission-focused solutions across energy, cyber, air, land, sea, and space domains. We combine the right people ...

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$83.2K

How much do remote machine learning jobs pay per year?

As of May 28, 2026, the average yearly pay for remote machine learning in Tucson, AZ is $40,262.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,700.00 and $43,500.00 per year, depending on experience, location, and employer.

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 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.

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 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.

Is ML full of coding?

Machine Learning (ML) roles often involve significant coding, especially in programming languages like Python or R, to develop algorithms and models. However, some positions focus more on data analysis, feature engineering, or model evaluation, which may require less coding but still involve technical skills and understanding of ML concepts.

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.

More about Remote Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in Tucson, AZ? The most popular types of Machine Learning jobs in Tucson, AZ are:
What job categories do people searching Remote Machine Learning jobs in Tucson, AZ look for? The top searched job categories for Remote Machine Learning jobs in Tucson, AZ are:
What cities near Tucson, AZ are hiring for Remote Machine Learning jobs? Cities near Tucson, AZ with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you
ML Administrator

ML Administrator

SOS International LLC

Tucson, AZ • Remote

Other

This job post has expired today. Applications are no longer accepted.

Job description

Remote, Remote, USA

Full-time

Clearance Requirement: None

Company Description

Founded in 1989, SOSi is among the largest private, founder-owned technology and services integrators in the defense and government services industry. We deliver tailored solutions, tested leadership, and trusted results to enable national security missions worldwide.

Job Description

This position is contingent upon award of contract

SOSi is seeking an ML Administrator to support mission requirements for a structured approach to further develop, integrate, and sustain a scalable, federated data ecosystem that enhances interoperability, governance, and mission-driven analytics for a DoD customer. The primary objective of the program is to bridge the operational gaps between DoD, IC, interagency, and non-traditional international partners to enable real-time information sharing, dynamic data integration, and mission-tailored analytical capabilities.

Essential Job Duties:

  • Manage machine learning model versioning, lineage tracking, and compliance with governance policies, ensuring reproducibility and secure deployment.

  • Implement and monitor ML infrastructure, optimizing compute resource allocation across cloud and on-premises environments.

  • Validation of AI/ML pipelines, ensuring models remain accurate, explainable, and aligned with operational objectives.

  • Manage ML Model Governance & Deployment Reporting including summarizing model lifecycle management, performance tracking, and security compliance.

Qualifications

  • Master's degree or higher (e.g., Ph.D.) in Computer Science, Information Technology, Systems Engineering, Data Science, Business Administration, Engineering Management, or a closely related field; OR minimum of 11+ years of experience managing complex technical projects in enterprise data architecture, Databricks administration, and cloud-based data platforms.

  • Databricks platform administration, including workspace management, workspace configuration, cluster optimization, cluster performance tuning, and Unity Catalog integration for secure data governance.

  • ETL/ELT pipeline development, Delta Lake architecture and optimization, and data lakehouse optimization for DoD analytics and mission-critical data workflows.

  • AI/ML workflow integration within Databricks environments.

  • SysEngOps and DevSecOps practices with version control systems (Git) and CI/CD pipelines for streamlined Databricks development, automated deployment, and governance.

  • Identity and access management (IAM), role-based access control (RBAC), cloud security best practices, and compliance with DoD data policies across AWS, Azure, and GCP.

  • Hands-on expertise in Python, SQL/NoSQL databases, Apache Spark, Databricks SQL, Terraform, and cloud-native data services for large-scale data processing and analytics.

  • Knowledge and capability to support Databricks platform administration and enterprise data architecture for DoD data-driven projects and mission-critical workflows.

Additional Information

Work Environment

  • Remote

Working at SOSi

All interested individuals will receive consideration and will not be discriminated against for any reason.

SOSi is an equal employment opportunity employer and affirmative action employer. All interested individuals will receive consideration and will not be discriminated against on the basis of race, color, religion, sex, national origin, disability, age, sexual orientation, gender identity, genetic information, or protected veteran status. SOSi takes affirmative action in support of its policy to advance diversity and inclusion of individuals who are minorities, women, protected veterans, and individuals with disabilities.

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