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Remote Machine Learning Jobs in Arizona (NOW HIRING)

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Strong foundations in modern machine learning, including deep learning, optimization ... Remote work, medical insurance, flexible time off, retirement savings plans, and modern family ...

New

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Strong foundations in modern machine learning, including deep learning, optimization ... Remote work, medical insurance, flexible time off, retirement savings plans, and modern family ...

New

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Strong foundations in modern machine learning, including deep learning, optimization ... Remote work, medical insurance, flexible time off, retirement savings plans, and modern family ...

New

Block

Strong foundations in modern machine learning, including deep learning, optimization ... Remote work, medical insurance, flexible time off, retirement savings plans, and modern family ...

New

Block

Strong foundations in modern machine learning, including deep learning, optimization ... Remote work, medical insurance, flexible time off, retirement savings plans, and modern family ...

New

Block

Strong foundations in modern machine learning, including deep learning, optimization ... Remote work, medical insurance, flexible time off, retirement savings plans, and modern family ...

New

NucleusTeq

Data Scientist

Phoenix, AZ · On-site +1

Develop and manage project roadmaps for AI and Machine Learning-driven products, ensuring timely delivery of features that leverage large-scale data models and AI systems; Lead cross-functional teams ...

Dutchbros

Lead Engineer, Data Platforms

Tempe, AZ · On-site +1

$111K - $133K/yr

... machine learning, and AI-driven workflows and will be responsible for designing and implementing ... Location Requirement: This position is eligible for remote work within any state Dutch Bros ...

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All JobsMachine Learning JobsRemote Machine Learning JobsRemote Machine Learning Jobs in Arizona

Remote Machine Learning information

See Arizona salary details

$23.8K

$39.7K

$82K

How much do remote machine learning jobs pay per year?

As of Sep 3, 2026, the average yearly pay for remote machine learning in Arizona is $39,683.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,300.00 and $42,900.00 per year, depending on experience, location, and employer.

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.

More about Remote Machine Learning jobs

What are the most commonly searched types of Machine Learning jobs in Arizona?

The most popular types of Machine Learning jobs in Arizona are:

What are popular job titles related to Remote Machine Learning jobs in Arizona?

For Remote Machine Learning jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Remote Machine Learning jobs in Arizona look for?

The top searched job categories for Remote Machine Learning jobs in Arizona are:

What cities in Arizona are hiring for Remote Machine Learning jobs?

Cities in Arizona with the most Remote Machine Learning job openings:

Remote Machine Learning jobs near you
Infographic showing various Remote Machine Learning job openings in Arizona as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 21% Part Time, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $39,683 per year, or $19.1 per hour.

Elastic Security Engineer (SIEM) - Active TS Clearance

Serviss

Sierra Vista, AZ • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 9 days ago

Job description

Elastic Security Engineer (SIEM)
Location: Sierra Vista, AZ / Remote
Employment Type: Full-TimeAbout SERVISS
At SERVISS, we deliver cutting-edge cybersecurity and IT solutions to government and commercial clients, with a mission to secure systems, data, and critical infrastructure through innovation and expertise. We don't just deploy tools; we engineer mission platforms that become foundational systems of record for cyber operations, compliance automation, and national cyber readiness. From CISA CDM to DoW mission enclaves, our work shapes how government sees, governs, and defends its digital terrain.
As a provider of managed cybersecurity services, SERVISS delivers a highly tailored offering to each customer. Our mission is broad and our teams are agile; we look to your unique skills to approach and solve problems in your own way, whether engineering a system to clear a technical hurdle, protecting customer data, or consulting across a wide range of security topics. You are empowered to engage and lead across multiple groups.
Position Summary
SERVISS is seeking an Elastic Security Engineer to support a Federal DoD SIEM program. This is a technical, hands-on role in which you will work within a multi-disciplined team to design, build, secure, maintain, optimize, and document multiple Elastic Stack enterprise solutions (Elasticsearch, Logstash, Kibana, Beats, Machine Learning, and SIEM) deployed globally in a Federal DoD environment, with automation support using Ansible.
You will perform continuous data-normalization functions and support the delivery of written technical deliverables such as SOPs and process workflows to optimize tool usage and contribute to new capabilities. Your infrastructure, data pipelines, and reporting automation will directly support internal engineering personnel and external customer requirements.
The Work
This is a hands-on engineering role. The selected candidate will:
  • Design, build, secure, maintain, optimize, and document multiple Elastic Stack enterprise solutions (Elasticsearch, Logstash, Kibana, Beats, Machine Learning, and SIEM) deployed globally in a Federal DoD environment
  • Automate deployment and configuration using Ansible playbooks
  • Perform continuous data-normalization functions across diverse data sources
  • Build data pipelines and reporting automation that directly support internal engineering personnel and external customer requirements
  • Author written technical deliverables such as SOPs and process workflows to optimize tool usage and contribute to new capabilities
Key Responsibilities
  • Support a Federal DoD SIEM program as part of a multi-disciplined engineering team
  • Maintain, optimize, and secure enterprise Elastic Stack solutions deployed globally
  • Contribute to new capabilities and the continuous improvement of tool usage
  • Engage and collaborate across engineering teams and customer stakeholders
Required Qualifications
  • Active Top Secret security clearance
  • US citizenship
  • Compliance with DoD 8140 / 8570 IAT Level II certification prior to start date
  • At least 4 years of hands-on experience in deployment, configuration, and solution development using the Elastic Stack for security and logging use cases (Elastic SIEM experience a plus)
  • Demonstrated experience with the full Elastic Stack: Elasticsearch, Logstash, Kibana, Beats, Machine Learning, and REST API integration
  • Demonstrated ability to use Ansible playbooks

Preferred Qualifications
  • Experience integrating Elasticsearch with external systems (e.g., SOAR tools, threat intelligence platforms)
  • Experience with data management: hot/warm/cold architectures, shard allocation and re-allocation, snapshots and restoration
  • Strong experience evaluating existing Elastic clusters, configuration parameters, indexing, search and query performance tuning, security, and cluster administration
  • Experience integrating Elasticsearch with authentication mechanisms such as SAML, LDAP, and PKI
  • Experience supporting the Elastic Stack in on-prem and SaaS environments, including system monitoring and tuning
  • Experience securing the Elastic Stack and hardening hosting environments
  • Development experience in multiple languages (Python, Bash, PowerShell, Painless, etc.)
  • Experience designing and implementing highly scalable Elastic Stack solutions
  • Experience developing data structures and data mappings from various sources to achieve data normalization using Elastic Common Schema (ECS)
  • Experience developing Logstash and/or ingest pipelines
  • Experience developing custom Kibana visualizations and dashboards
  • Experience developing custom reporting solutions using APIs that leverage Elasticsearch and ElastiCache
  • Experience with end-to-end low-level design, development, administration, and delivery of Elasticsearch-based reporting solutions
  • Strong technical foundation in building reliable, scalable, and supportable systems
  • Experience with Red Hat Enterprise Linux deployment and administration
Freedom to Thrive.
Why Join SERVISS? Our goal as an employer is simple yet profound: to create an environment where you can be your best self, pursue your passions, and enjoy the freedom to thrive both personally and professionally. Your success is our success, and we're committed to supporting you every step of the way.
  • Highly competitive compensation and best in class benefits
  • 100% of medical, vision, dental, and life insurance premiums paid for by SERVISS
  • Be part of an exciting company with ground floor opportunities in the Equity Participation Program
  • Opportunities for annual performance bonuses and growth incentives
  • 401(k) retirement plan with 6% dollar for dollar match
Additional Considerations for HUBZone applicants:
Preference may be given to applicants residing in a federal HUBZone in support of SERVISS LLC's HUBZone workforce objectives; all qualified candidates are encouraged to apply.
How to Determine HUBZone Residency:
Candidates can verify HUBZone eligibility by entering their home address into the SBA HUBZone Map at https://maps.certify.sba.gov/hubzone/map. If your residence falls within a designated HUBZone area on the map, you are considered a HUBZone resident for hiring preference purposes.

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