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Remote Full Stack Machine Learning Engineer Jobs in Arizona

Varsity Tutors

Machine Learning Tutor

Scottsdale, AZ · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Glendale, AZ · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Tempe, AZ · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Phoenix, AZ · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Chandler, AZ · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Gilbert, AZ · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Tucson, AZ · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Mesa, AZ · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Provn

Agentic Software Engineer II

Scottsdale, AZ · Remote

$119K - $188K/yr

Develop and deliver features and services for the travel platform on a full-stack product ... a remote-friendly culture that spans US and international time zones. How to Apply To apply for ...

Phoenix Staff

Lead Data & AI Engineer

Phoenix, AZ · On-site +1

$50 - $60/hr

... machine learning models that improve cost, quality, and patient outcomes. Your role · Design ... full lineage and governance. · Develop secure data environments that comply with HIPAA and PHI ...

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All JobsFull Stack Machine Learning Engineer JobsRemote Full Stack Machine Learning Engineer JobsRemote Full Stack Machine Learning Engineer Jobs in Arizona

Remote Full Stack Machine Learning Engineer information

What is a remote full stack machine learning engineer?

A Remote Full Stack Machine Learning Engineer is a professional who designs, develops, and deploys machine learning solutions while working remotely. They handle both the front-end and back-end aspects of machine learning projects, including data preprocessing, model building, API development, and integration with user interfaces or cloud platforms. This role requires expertise in programming, machine learning frameworks, cloud services, and web technologies, allowing them to build end-to-end AI-driven applications from anywhere in the world.

What are the key skills and qualifications needed to thrive as a remote full stack machine learning engineer?

To thrive as a Remote Full Stack Machine Learning Engineer, you need proficiency in programming languages (such as Python or JavaScript), a solid understanding of machine learning algorithms, experience with web development frameworks, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, Docker, cloud computing platforms (AWS, GCP), and version control systems (Git) is essential. Strong problem-solving skills, self-motivation, and clear communication are crucial soft skills, especially in remote and cross-functional team environments. These combined skills ensure effective design, deployment, and integration of machine learning solutions in scalable web applications while maintaining productivity in a remote setting.

What are some common challenges faced by remote full stack machine learning engineers, and how can they be addressed?

Remote Full Stack Machine Learning Engineers often encounter challenges such as managing effective collaboration with cross-functional teams and ensuring smooth deployment of machine learning models into production environments. To address these, it's important to establish clear communication channels, regularly participate in virtual stand-ups, and use collaborative platforms such as GitHub and Slack. Additionally, staying organized with version control and thorough documentation helps maintain project transparency and ensures seamless handoffs between backend and frontend development. Proactively seeking feedback and scheduling regular check-ins with team members can further enhance productivity and integration within the team.

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

AspectRemote Full Stack Machine Learning EngineerRemote Data Scientist
Primary FocusDeveloping end-to-end machine learning applications, including backend, frontend, and model deploymentAnalyzing data, creating models, and generating insights without necessarily building full applications
Skills RequiredProgramming (Python, JavaScript), ML frameworks, web development, deployment toolsStatistics, data analysis, visualization, Python/R, SQL
Work EnvironmentCollaborates with developers, data engineers, and product teams in tech-driven companiesWorks with data teams, analysts, and business units in various industries

While both roles involve working with data and machine learning, a Remote Full Stack Machine Learning Engineer builds complete applications with integrated ML models, whereas a Remote Data Scientist focuses on data analysis and model creation without necessarily developing full applications.

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

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

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

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

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

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

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

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

Remote Full Stack Machine Learning Engineer jobs near you

Elastic Security Engineer (SIEM) - Active TS Clearance

Serviss

Sierra Vista, AZ • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 25 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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