Remote Machine Learning Engineer Jobs
Remote Machine Learning Engineer jobs are in strong demand at remote-first firms and distributed engineering teams across technology, finance, and healthcare. Employers hiring remotely right now include Atlassian, Whatnot, and BV Teck. See the openings below and apply to the ones that match your experience.
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US Based Position. Must be US Citizen.
Location: Arlington VA(U.S.-based). Remote Work Allowed in US.
Employment Type: Full-Time
Company: Technology & Business Management, Inc. (TBM Inc.)
Experience Level
8+ years in security analytics/SIEM engineering with 4+ years of advanced Splunk engineering; hands-on dashboarding, SPL, alerting, data onboarding, and automation required.
Position Summary
Own DLP telemetry, analytics, dashboards, alerting, automation, and measurable optimization in Splunk, while supporting Government-approved SOAR/RPA and bounded AI/ML use cases.
Key Responsibilities
Engineer and maintain Splunk ingestion, normalization, searches, dashboards, reports, alerts, health metrics, event-volume trends, and operational/executive DLP reporting.
Develop SPL queries and documented calculations that Government personnel can reproduce and sustain.
Integrate telemetry from Symantec/Broadcom, Purview, Palo Alto, and other authorized DLP/security platforms.
Design automated notifications, alerts, alarms, and Government-authorized SOAR/RPA workflows to reduce manual triage and improve response.
Support event correlation, incident analytics, severity/prioritization, trend analysis, and detection-performance measurement.
Evaluate approved AI/ML-enabled capabilities to reduce false positives, identify notable events, improve triage, and reduce analyst workload; establish baseline/candidate comparisons and rollback criteria.
Track metrics such as false positives, false negatives where measurable, alert volume, time-to-triage/disposition, stability, workload, and business impact.
Document data definitions, dashboard maintenance, automation logic, model/configuration tuning, test evidence, limitations, procedures, and Government training.
Required / Critical Skills
Splunk Enterprise / Splunk ES; SPL; dashboards; data models; alerts; field extraction; ingestion/onboarding; CIM; APIs; security analytics; incident correlation.
Splunk SOAR or comparable orchestration/automation; Python or scripting; REST APIs; JSON; data normalization.
Understanding of DLP events/policies, SOC workflows, detection engineering, false-positive reduction, and security KPIs.
Practical AI/ML analytics knowledge with emphasis on explainability, human review, validation, privacy/security controls, and measurable benefit rather than custom model research.
Splunk Core Certified Power User/Admin/Architect or Splunk Enterprise Security certification strongly preferred.
Preferred Qualifications
Experience with Qmulos, federal continuous monitoring/FISMA reporting, or large federal Splunk environments.
Experience integrating DLP products into SIEM/SOAR workflows.
Current Public Trust/MBI or clearance.
Education
Bachelor’s degree in Cybersecurity, Information Technology, Computer Science, Engineering, Information Systems, or a related field is preferred. Equivalent directly relevant experience and advanced industry certifications may be considered, subject to the applicable contract labor-category requirements.
Federal Suitability / Security
Candidate must be able to meet IRS personnel-security and suitability requirements for the position, including the applicable background investigation and required security/privacy training. A current favorably adjudicated federal Public Trust/MBI or other investigation that may qualify for reciprocity is highly desirable.
What Will Make a Candidate Stand Out
Direct hands-on experience with the named platform(s), not only governance or oversight.
Recent enterprise production experience supporting sensitive or regulated information.
Ability to explain specific examples of troubleshooting, policy/rule tuning, testing, incident support, measurable improvement, and documentation.
Federal customer experience and demonstrated ability to work within controlled access, change, audit, and documentation processes.
Ability to become productive quickly and communicate effectively with both engineers and Government stakeholders.
Why Join TBM Inc.
- Support high-impact federal missions
- Work on strategic IT modernization programs
- Join a fast-growing federal consulting firm
- Collaborate with experienced government and industry leaders
- Opportunity to grow into senior consulting and portfolio management roles
How to Apply
Interested candidates should apply via Indeed with their resume. Qualified applicants will be contacted for next steps.
TBM Inc. is an equal opportunity employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, disability, or veteran status.
Job Type: Full-time
Pay: $145,000.00 - $155,000.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Employee assistance program
- Employee discount
- Flexible schedule
- Flexible spending account
- Health insurance
- Health savings account
- Life insurance
- Paid time off
- Professional development assistance
- Referral program
- Retirement plan
- Tuition reimbursement
- Vision insurance
Work Location: Remote
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Find JobsRemote Machine Learning Engineer Job Market
Who's Hiring
- Atlassian14
- Whatnot7
- BV Teck6
- Amgen5
- Airbnb5
Top Industries Hiring
- Technology & Software31
- Automotive7
- Hospitality & Tourism6
- Consulting & Professional Services6
- Banking & Financial Services3
What Employers Look For
The qualifications that appear most often in remote machine learning engineer jobs.
- Proficiency in Python and ML frameworks such as PyTorch or TensorFlow
- Experience building and deploying models in cloud environments like AWS, GCP, or Azure
- Familiarity with MLOps tools including MLflow, Kubeflow, or SageMaker
- Strong foundation in statistics, linear algebra, and machine learning theory
- Bachelor's or master's degree in computer science, mathematics, or a related field
- Experience with large-scale data processing using Spark, SQL, or distributed systems
Tips for Your Remote Machine Learning Engineer Job Search
Apply early to remote roles that fit
Migrate Mate lists remote machine learning engineer openings from companies hiring across the U.S. in one place. Check it regularly and apply directly to roles that match your stack and experience level before postings fill.
Show async collaboration in your portfolio
Remote machine learning teams rely on written documentation over verbal updates. Include README files, experiment logs, and model cards in your GitHub projects so hiring managers can evaluate your reasoning without a walkthrough call.
Demonstrate experiment tracking and reproducibility
Remote ML employers screen for candidates who manage their own workflows without oversight. Showcase your use of tools like MLflow, DVC, or Weights and Biases to show you can run structured, reproducible experiments independently in a distributed environment.
Target remote-first companies in your search
Remote-first software firms and AI-native startups have built distributed engineering cultures from the ground up. These employers are more likely to have remote-specific onboarding, async code review processes, and the tooling that makes remote machine learning work sustainable long-term.
Remote Machine Learning Engineer Jobs: Frequently Asked Questions
How do I get a remote machine learning engineer job?
Target companies with established remote engineering cultures, such as remote-first software firms and distributed product teams, because they've already built the infrastructure for async collaboration. Remote employers screen for self-direction, clear written communication, and the ability to document model decisions and experiments without hand-holding. A strong GitHub presence, reproducible notebooks, and demonstrated experience with MLflow, DVC, or similar experiment-tracking tools give candidates a concrete edge over the competition.
Which companies hire remote machine learning engineers?
Companies hiring remote machine learning engineers right now include Atlassian, Whatnot, and BV Teck, based on current remote listings on Migrate Mate as of September 2026. Remote openings for this role are concentrated at remote-first software companies, AI-native startups, and distributed teams in fintech, healthtech, and enterprise SaaS.
Can you get a remote machine learning engineer job with no experience?
Yes, but remote entry-level machine learning engineer roles are harder to land because you're expected to work independently from day one with minimal in-person guidance. The most effective path is building a public portfolio of end-to-end ML projects on GitHub, contributing to open-source model repositories, or completing structured ML engineering programs. Remote-first startups and research-oriented companies are the most likely to hire junior candidates who can demonstrate initiative through real, documented work.
Do you need a degree for remote machine learning engineer jobs?
Not always. Many remote employers weigh a candidate's GitHub portfolio, demonstrated proficiency with frameworks like PyTorch or TensorFlow, and real project outcomes more heavily than a formal credential. That said, roles at enterprise firms and research-driven organizations often list a degree in computer science, statistics, or a related field as a baseline. Candidates without a degree strengthen their position by showing deployed models, clear experiment documentation, and measurable results from real projects.
Which industries hire the most remote machine learning engineers?
The sectors hiring the most remote machine learning engineers are Technology & Software, Automotive, and Hospitality & Tourism, based on current remote listings on Migrate Mate as of September 2026. These industries rely on distributed engineering teams and have the data infrastructure and product demands that make remote machine learning work both practical and scalable.
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