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Manager Remote Machine Learning Engineer Jobs in Sierra Vista, AZ

CPS, LLC

Senior Systems Engineer (OOBM)

Sierra Vista, AZ · Remote

$93K - $127K/yr

... Engineer - Senior, you will provide services in support of the U.S. Army Network Enterprise ... remote management and messaging capabilities in support of the Army and Joint NetOps initiatives ...

All JobsMachine Learning Engineer JobsManager Remote Machine Learning Engineer JobsManager Remote Machine Learning Engineer Jobs in Sierra Vista, AZ

Manager Remote Machine Learning Engineer information

See Sierra Vista, AZ salary details

$27.1K

$61K

$102.8K

How much do manager remote machine learning engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for manager remote machine learning engineer in Sierra Vista, AZ is $61,050.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,300.00 and $66,300.00 per year, depending on experience, location, and employer.

What is a manager remote machine learning engineer?

A Manager Remote Machine Learning Engineer is a leadership role responsible for overseeing a team of machine learning engineers who work remotely. They manage the development, deployment, and optimization of machine learning models and ensure that projects align with organizational goals. In addition to technical expertise, this manager focuses on remote team collaboration, communication, and productivity. They often coordinate workflows, mentor team members, and act as a bridge between technical teams and business stakeholders.

How does a manager remote machine learning engineer typically balance team leadership with hands-on technical responsibilities?

A Manager Remote Machine Learning Engineer often splits time between leading and mentoring a distributed team and actively contributing to machine learning projects. While overseeing project timelines, conducting code reviews, and setting technical direction are key leadership tasks, managers also stay involved in model development and troubleshooting to maintain technical expertise. Effective communication and clear documentation are crucial, as remote teams rely on these to collaborate efficiently across different time zones. Balancing these responsibilities requires strong organizational skills and the ability to prioritize both people management and technical deliverables.

What are the key skills and qualifications needed to thrive as a manager remote machine learning engineer, and why are they important?

To thrive as a Manager Remote Machine Learning Engineer, strong expertise in machine learning algorithms, programming (Python, R), and a degree in computer science or a related field are essential, along with proven leadership experience. Familiarity with cloud platforms (AWS, Azure, GCP), ML frameworks (TensorFlow, PyTorch), and project management tools is typically required, as well as certifications such as AWS Certified Machine Learning or Google Professional Machine Learning Engineer. Outstanding communication, team leadership, and problem-solving skills help foster collaboration and drive remote teams toward project goals. These capabilities are vital for effectively managing distributed teams, delivering robust AI solutions, and ensuring project success in a remote environment.

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

AspectManager Remote Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience in ML engineeringBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentRemote, collaborative teams, focus on ML model deploymentRemote or on-site, data analysis, model development, research
Employer & Industry UsageTech companies, AI startups, large enterprisesTech, finance, healthcare, research institutions
Search & Comparison IntentUnderstanding managerial roles in ML teamsData analysis, modeling, research tasks

The Manager Remote Machine Learning Engineer oversees ML projects and teams, focusing on deployment and management, while Data Scientists primarily analyze data and develop models. Both roles require strong technical skills, but the manager role emphasizes leadership and project oversight.

Can a manager remote machine learning engineer work remotely?

Yes, a manager remote machine learning engineer can work remotely, as many companies offer remote positions for this role. Success in remote work often depends on strong communication skills, familiarity with collaboration tools, and the ability to manage projects independently.

What job categories do people searching Manager Remote Machine Learning Engineer jobs in Sierra Vista, AZ look for?

The top searched job categories for Manager Remote Machine Learning Engineer jobs in Sierra Vista, AZ are:

What cities near Sierra Vista, AZ are hiring for Manager Remote Machine Learning Engineer jobs?

Cities near Sierra Vista, AZ with the most Manager Remote Machine Learning Engineer job openings:

Manager Remote Machine Learning Engineer jobs near you
Infographic showing various Manager Remote Machine Learning Engineer job openings in Sierra Vista, AZ as of August 2026, with employment types broken down into 84% Full Time, 15% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $61,050 per year, or $29.4 per hour.

Elastic Security Engineer (SIEM) - Active TS Clearance

Serviss

Sierra Vista, AZ • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 22 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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