Remote AI Engineer Jobs
Remote AI Engineer jobs are open across the U.S. at remote-first companies and distributed teams in sectors like software, fintech, healthcare technology, and enterprise SaaS. Employers hiring remotely right now include CVS Health, Advanced Monitored Caregiving, and BV Teck. Find a role that fits below and apply directly.
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About Bitdeer Technologies Group
Bitdeer is a world-leading technology company for AI and Bitcoin mining infrastructure.
Bitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers and building AI computational infrastructure to support the AI revolution. Bitdeer handles complex processes involved in computing such as equipment procurement, transport logistics, data center design and construction, equipment management, and daily operations. Bitdeer also offers advanced cloud capabilities to customers with high demand for artificial intelligence.
Headquartered in Singapore, Bitdeer has deployed data centers across multiple countries, including the United States, Norway, Bhutan, and Ethiopia.
To learn more, visit https://ir.bitdeer.com/
Position Summary:
We are seeking a highly skilled and motivated Cloud Senior DevOps Engineer to join our AI Cloud team. In this high-impact role, you will be the backbone of our deployment and infrastructure operations, ensuring that our AI-powered products and platforms are delivered with speed, security, and exceptional reliability. You will act as a crucial bridge between our research/development teams and real-world deployment, driving automation, optimizing cloud-native architectures, and establishing best practices for MLOps and traditional DevOps workflows.
Key Responsibilities:
- CI/CD & MLOps Pipeline Management: Design, implement, and maintain end-to-end CI/CD pipelines for both software applications and machine learning models. Automate build, test, deployment, and rollback processes to ensure seamless transitions from innovation to production.
- Cloud-Native & AI Infrastructure: Build, optimize, and scale cloud-native infrastructure using Kubernetes (K8s) and Docker. Manage and provision specialized computing resources (e.g., GPU clusters) to support high-performance AI workloads and model inferencing.
- High Availability Architecture: Take ownership of high-availability design in production environments. Implement disaster recovery (DR) strategies, self-healing mechanisms, capacity planning, and performance tuning to meet stringent business SLAs.
- Infrastructure as Code (IaC): Champion IaC practices utilizing tools such as Terraform, Ansible, and Helm to achieve fully automated, reproducible, and auditable infrastructure provisioning across multiple cloud environments.
- Observability & Monitoring: Architect and refine comprehensive monitoring, logging, and alerting systems (e.g., Prometheus, Grafana, ELK/EFK stack) to provide deep visibility into system health, application performance, and AI model metrics.
- Cross-functional Collaboration: Work closely with R&D, Data Science, Security, and Business teams to streamline workflows, eliminate bottlenecks, and continuously elevate engineering efficiency through Internal Developer Platforms (IDP) and Platform Engineering initiatives.
- Governance, Security & Compliance: Establish and enforce robust system stability and security standards. Manage release workflows, implement Zero Trust access controls, oversee secrets management, and ensure compliance with industry frameworks (e.g., SOC2, ISO27001).
- Incident Management & Resolution: Act as the technical lead during complex system anomalies and major incidents. Spearhead rapid troubleshooting, conduct thorough root cause analysis (RCA), and implement preventative remediation plans.
Basic Qualifications:
- Experience & Education: Bachelor's degree or above in Computer Science, Engineering, or a related technical field, with 5+ years of hands-on experience in DevOps, Site Reliability Engineering (SRE), or Cloud Infrastructure roles.
- Networking & OS: Expert-level knowledge of Linux operating systems and core networking principles (TCP/IP, DNS, HTTP, Load Balancing, VPCs).
- Containerization & Orchestration: Deep mastery of Docker and Kubernetes orchestration, including a thorough understanding of underlying principles, cluster management, and production-level best practices.
- Cloud Platforms: Proven proficiency in designing and managing infrastructure on major Public or Hybrid Cloud platforms (e.g., AWS, GCP, Azure, Alibaba Cloud), including multi-cloud and hybrid-cloud strategies.
- Programming Skills: Strong coding and scripting capabilities in at least one major language (Go, Python, Shell, etc.) with a solid engineering-oriented mindset focused on automation and tooling development.
- Domain Knowledge: Systematic and practical understanding of CI/CD methodologies, Infrastructure as Code (IaC), Observability paradigms, and Site Reliability Engineering (SRE) principles.
- Soft Skills: Exceptional problem-solving abilities, sharp technical judgment, and excellent cross-team communication skills to effectively collaborate in a fast-paced, dynamic environment.
Preferred Qualifications (Plus):
- AI/ML Infrastructure Experience: Familiarity with MLOps practices, model serving/inferencing frameworks (e.g., vLLM, TGI, Triton Inference Server), and experience managing GPU clusters for AI/ML workloads.
- Large-Scale Systems: Proven track record working with large-scale distributed systems or high-concurrency environments (e.g., Fintech, Trading, Real-time processing, or AI platforms).
- Platform Engineering: Hands-on experience in designing and building Internal Developer Platforms (IDP) to enhance developer autonomy and productivity.
- Advanced Security: Deep familiarity with Zero Trust architecture, automated security testing (DevSecOps), and implementing strict compliance frameworks (e.g., SOC2, ISO27001).
- Leadership: Prior experience acting as a Technical Lead, mentoring junior engineers, or managing DevOps teams.
-
Bitdeer is committed to providing equal employment opportunities in accordance with country, state, and local laws. Bitdeer does not discriminate against employees or applicants based on conditions such as race, color, gender identity and/or expression, sexual orientation, marital and/or parental status, religion, political opinion, nationality, ethnic background or social origin, social status, disability, age, indigenous status, and union.
About Bitdeer Technologies Group
Bitdeer is a world-leading technology company for AI and Bitcoin mining infrastructure.
Bitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers and building AI computational infrastructure to support the AI revolution. Bitdeer handles complex processes involved in computing such as equipment procurement, transport logistics, data center design and construction, equipment management, and daily operations. Bitdeer also offers advanced cloud capabilities to customers with high demand for artificial intelligence.
Headquartered in Singapore, Bitdeer has deployed data centers across multiple countries, including the United States, Norway, Bhutan, and Ethiopia.
To learn more, visit https://ir.bitdeer.com/
Position Summary:
We are seeking a highly skilled and motivated Cloud Senior DevOps Engineer to join our AI Cloud team. In this high-impact role, you will be the backbone of our deployment and infrastructure operations, ensuring that our AI-powered products and platforms are delivered with speed, security, and exceptional reliability. You will act as a crucial bridge between our research/development teams and real-world deployment, driving automation, optimizing cloud-native architectures, and establishing best practices for MLOps and traditional DevOps workflows.
Key Responsibilities:
- CI/CD & MLOps Pipeline Management: Design, implement, and maintain end-to-end CI/CD pipelines for both software applications and machine learning models. Automate build, test, deployment, and rollback processes to ensure seamless transitions from innovation to production.
- Cloud-Native & AI Infrastructure: Build, optimize, and scale cloud-native infrastructure using Kubernetes (K8s) and Docker. Manage and provision specialized computing resources (e.g., GPU clusters) to support high-performance AI workloads and model inferencing.
- High Availability Architecture: Take ownership of high-availability design in production environments. Implement disaster recovery (DR) strategies, self-healing mechanisms, capacity planning, and performance tuning to meet stringent business SLAs.
- Infrastructure as Code (IaC): Champion IaC practices utilizing tools such as Terraform, Ansible, and Helm to achieve fully automated, reproducible, and auditable infrastructure provisioning across multiple cloud environments.
- Observability & Monitoring: Architect and refine comprehensive monitoring, logging, and alerting systems (e.g., Prometheus, Grafana, ELK/EFK stack) to provide deep visibility into system health, application performance, and AI model metrics.
- Cross-functional Collaboration: Work closely with R&D, Data Science, Security, and Business teams to streamline workflows, eliminate bottlenecks, and continuously elevate engineering efficiency through Internal Developer Platforms (IDP) and Platform Engineering initiatives.
- Governance, Security & Compliance: Establish and enforce robust system stability and security standards. Manage release workflows, implement Zero Trust access controls, oversee secrets management, and ensure compliance with industry frameworks (e.g., SOC2, ISO27001).
- Incident Management & Resolution: Act as the technical lead during complex system anomalies and major incidents. Spearhead rapid troubleshooting, conduct thorough root cause analysis (RCA), and implement preventative remediation plans.
Basic Qualifications:
- Experience & Education: Bachelor's degree or above in Computer Science, Engineering, or a related technical field, with 5+ years of hands-on experience in DevOps, Site Reliability Engineering (SRE), or Cloud Infrastructure roles.
- Networking & OS: Expert-level knowledge of Linux operating systems and core networking principles (TCP/IP, DNS, HTTP, Load Balancing, VPCs).
- Containerization & Orchestration: Deep mastery of Docker and Kubernetes orchestration, including a thorough understanding of underlying principles, cluster management, and production-level best practices.
- Cloud Platforms: Proven proficiency in designing and managing infrastructure on major Public or Hybrid Cloud platforms (e.g., AWS, GCP, Azure, Alibaba Cloud), including multi-cloud and hybrid-cloud strategies.
- Programming Skills: Strong coding and scripting capabilities in at least one major language (Go, Python, Shell, etc.) with a solid engineering-oriented mindset focused on automation and tooling development.
- Domain Knowledge: Systematic and practical understanding of CI/CD methodologies, Infrastructure as Code (IaC), Observability paradigms, and Site Reliability Engineering (SRE) principles.
- Soft Skills: Exceptional problem-solving abilities, sharp technical judgment, and excellent cross-team communication skills to effectively collaborate in a fast-paced, dynamic environment.
Preferred Qualifications (Plus):
- AI/ML Infrastructure Experience: Familiarity with MLOps practices, model serving/inferencing frameworks (e.g., vLLM, TGI, Triton Inference Server), and experience managing GPU clusters for AI/ML workloads.
- Large-Scale Systems: Proven track record working with large-scale distributed systems or high-concurrency environments (e.g., Fintech, Trading, Real-time processing, or AI platforms).
- Platform Engineering: Hands-on experience in designing and building Internal Developer Platforms (IDP) to enhance developer autonomy and productivity.
- Advanced Security: Deep familiarity with Zero Trust architecture, automated security testing (DevSecOps), and implementing strict compliance frameworks (e.g., SOC2, ISO27001).
- Leadership: Prior experience acting as a Technical Lead, mentoring junior engineers, or managing DevOps teams.
-
Bitdeer is committed to providing equal employment opportunities in accordance with country, state, and local laws. Bitdeer does not discriminate against employees or applicants based on conditions such as race, color, gender identity and/or expression, sexual orientation, marital and/or parental status, religion, political opinion, nationality, ethnic background or social origin, social status, disability, age, indigenous status, and union.
See All 601+ Remote AI Engineer Jobs
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Find Remote AI Engineer JobsRemote AI Engineer Job Market
Who's Hiring
- CVS Health58
- Advanced Monitored Caregiving27A
- BV Teck23
- General Motors (GM)8
- Revstar7
Top Industries Hiring
- Healthcare & Medical Services58
- Technology & Software54
- Consulting & Professional Services17
- Insurance8
- Automotive5
What Employers Look For
The qualifications that appear most often in remote AI engineer jobs.
- Proficiency in Python and at least one deep learning framework such as PyTorch or TensorFlow
- Experience designing, training, and deploying machine learning models in production environments
- Familiarity with cloud platforms such as AWS, Google Cloud, or Azure for ML workloads
- Understanding of LLM architectures, prompt engineering, and fine-tuning or RLHF techniques
- Bachelor's or master's degree in computer science, machine learning, statistics, or a related field
- Experience with MLOps tooling including experiment tracking, model versioning, and pipeline orchestration
Tips for Your Remote AI Engineer Job Search
Build a portfolio employers can review async
Remote hiring moves fast and asynchronously. Host your model projects, notebooks, and deployment work on GitHub with clear README files explaining your approach, the problem you solved, and the results. Reviewers assess your thinking before they ever speak to you.
Signal async communication skills upfront
Remote ai engineer teams communicate through Slack, Notion, Confluence, and written design docs rather than hallway conversations. Mention specific async tools and practices in your resume and cover letter so hiring managers can see you already work this way.
Apply early to remote roles that fit
Migrate Mate lists remote ai engineer openings from across the U.S. in one place so you can find roles that match your stack and apply directly. Remote postings fill quickly, so applying in the first few days gives you a real edge over later applicants.
Target companies with distributed engineering teams
Remote-first companies and those with established distributed teams have hiring processes built for remote candidates. Look for organizations where remote is the default, not an exception, since their onboarding, tooling, and management practices are already designed around distributed work.
Remote AI Engineer Jobs: Frequently Asked Questions
How do I get a remote ai engineer job?
Remote ai engineer roles go to candidates who can demonstrate strong async communication, self-directed work habits, and ownership of end-to-end ML pipelines without daily hand-holding. Remote employers screen hard for written clarity, documentation habits, and proficiency with tools like Git, Docker, and cloud platforms such as AWS or GCP. A public portfolio of shipped models or open-source contributions signals remote readiness far more than a polished resume alone.
Which companies hire remote ai engineers?
Remote ai engineer roles are posted by CVS Health, Advanced Monitored Caregiving, and BV Teck and others right now, based on current remote listings on Migrate Mate as of August 2026. Remote-first software companies, distributed fintech teams, and healthtech organizations make up the bulk of employers hiring ai engineers fully remotely.
Can you get a remote ai engineer job with no experience?
Yes, but remote entry-level ai engineer roles are harder to land because employers expect you to troubleshoot and iterate independently from day one. The companies most likely to hire entry-level remote ai engineers are early-stage startups and research-oriented firms willing to invest in growth. A strong GitHub profile, a completed capstone project, or a Kaggle competition result can substitute for formal work history and open the door.
Do you need a degree for remote ai engineer jobs?
Not always. Many remote employers care more about what you have shipped than where you studied, especially at startups and product-led companies hiring distributed teams. Demonstrated skills in Python, PyTorch or TensorFlow, and model deployment, backed by a visible project portfolio, carry real weight alongside or instead of a formal computer science or machine learning degree.
Which industries hire the most remote ai engineers?
The sectors hiring the most remote ai engineers are Healthcare & Medical Services, Technology & Software, and Consulting & Professional Services, based on current remote listings on Migrate Mate as of August 2026. These industries rely on distributed engineering teams and build AI-driven products that don't require engineers to be on-site, making remote work a natural fit for the role.
See All 601+ Remote AI Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Remote AI Engineer Jobs