Remote AI ML Engineer Jobs
Remote AI ML Engineer jobs are in strong demand across the U.S., with remote-first firms and distributed engineering teams actively hiring for roles in technology, finance, healthcare, and enterprise software. Employers hiring remotely right now include Truveta, Amgen, and Meridial. See the openings below and apply to the ones that match your experience.
Find Remote AI ML Engineer JobsOverview
Showing 5 of 45+ Remote AI ML Engineer jobs
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
See All 45 Remote AI ML Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Remote AI ML Engineer JobsRemote AI ML Engineer Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- Consulting & Professional Services
What Employers Look For
The qualifications that appear most often in remote AI ML engineer jobs.
- Proficiency in Python and at least one ML framework such as PyTorch or TensorFlow
- Experience designing, training, and deploying machine learning models in production environments
- Strong foundation in statistics, linear algebra, and probability theory
- Familiarity with MLOps tools and platforms including Kubeflow, MLflow, or SageMaker
- Experience working with large datasets using SQL, Spark, or distributed computing frameworks
- Bachelor's or master's degree in computer science, mathematics, or a related quantitative field
Tips for Your Remote AI ML Engineer Job Search
Apply early to remote roles that fit
Migrate Mate lists remote ai ml engineer openings from across the U.S. in one place, so you can find roles that match your skills and apply directly before postings fill. Remote roles at well-known companies often close faster than on-site equivalents.
Show async work samples upfront
Remote ai ml engineering teams evaluate written communication as seriously as model accuracy. Link directly to a model card, a Jupyter notebook with clear markdown reasoning, or a concise technical write-up in your application so reviewers can assess your thinking without a call.
Highlight MLOps and remote tooling experience
Distributed teams want engineers who can deploy, monitor, and iterate on models without daily standups. Calling out hands-on experience with tools like MLflow, Weights and Biases, Airflow, or cloud-based feature stores signals you can operate effectively in an async, remote-first environment.
Prepare for asynchronous take-home screens
Remote ai ml engineer interviews often replace live coding rounds with take-home model challenges or async code reviews. Practice completing a realistic ML problem, documenting your reasoning clearly, and committing clean, reproducible code, because that submission is often your first real impression.
Remote AI ML Engineer Jobs: Frequently Asked Questions
How do I get a remote ai ml engineer job?
Remote ai ml engineer roles go to candidates who can demonstrate self-direction and strong async communication alongside technical depth. Remote-first companies and distributed product teams hire heavily from open-source contributors, Kaggle competitors, and engineers with published model work or documented MLOps pipelines. Written clarity matters as much as model performance, because your thinking has to land without a whiteboard.
Which companies hire remote ai ml engineers?
Remote ai ml engineer roles are posted by Truveta, Amgen, and Meridial and others right now, based on current remote listings on Migrate Mate as of September 2026. Remote-first technology companies, distributed fintech teams, and enterprise software firms make up the bulk of remote ai ml engineer hiring.
Can you get a remote ai ml engineer job with no experience?
Yes, but remote entry-level ai ml engineer roles are harder to land because you're expected to work independently from day one without in-person mentorship. Smaller remote-first startups and early-stage AI companies are the most realistic entry points. A portfolio of end-to-end ML projects, contributions to public repositories, or a deployed model you can walk through in an async take-home will open more doors than a blank resume.
Do you need a degree for remote ai ml engineer jobs?
Not always. Remote employers weigh practical skills, published work, and demonstrated results heavily for ai ml engineer roles, especially at growth-stage companies. A strong GitHub history, verifiable Kaggle rankings, or production model experience can offset the absence of a formal degree, though larger enterprise teams often list a degree as a baseline requirement for senior roles.
Which industries hire the most remote ai ml engineers?
The sectors hiring the most remote ai ml engineers are Technology & Software and Consulting & Professional Services, based on current remote listings on Migrate Mate as of September 2026. Those sectors rely on distributed engineering teams that build, retrain, and monitor models without requiring engineers to be on-site.
See All 45 Remote AI ML Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Remote AI ML Engineer Jobs