Remote Machine Learning Jobs
Remote machine learning jobs are in active demand across the U.S., with remote-first firms and distributed engineering teams hiring for roles in tech, finance, healthcare, and AI research. Employers hiring remotely right now include Block, CVS Health, and Jobot. See the openings below and apply to the ones that match your experience.
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INTRODUCTION
Kforce has a client in Austin, TX that is seeking a Machine Learning & AI Infrastructure Engineer. This is not a traditional AI Engineer or Data Scientist role. The hiring team is specifically seeking a unique blend of: HPC Administrator + Kubernetes Administrator + AI Infrastructure Operations Engineer. Candidates who have owned, operated, supported, and troubleshot production AI or HPC environments will be the strongest fit. Experience administering and maintaining systems is significantly more important than architecture-only experience.
Responsibilities
- Administer and support AI and HPC cluster environments
- Manage day-to-day operations of large-scale compute infrastructure
- Deploy, maintain, and troubleshoot Kubernetes-based platforms
- Ensure reliability, performance, and scalability across compute, storage, and networking environments
- Support AI model training and inference infrastructure
- Automate operational processes through scripting and tooling
- Partner with engineering teams and customers to optimize platform performance
- Troubleshoot complex infrastructure, networking, storage, and containerization issues
- Support both internal platforms and customer-facing environments
Why Consider This Opportunity?
- 100% Remote Environment
- Exposure to cutting-edge AI, GenAI, and HPC technologies
- Flat organizational structure with minimal bureaucracy
- Direct impact on strategic technology initiatives
- Opportunity to work on platforms that support healthcare, research, drug discovery, and other meaningful AI-driven innovations
- High visibility and collaboration with industry-leading technical teams
COMPENSATION & BENEFITS
- Base Salary: $175,000 - $200,000+
- Annual Bonus: Typically 10%-15%
- Medical, Dental, and Vision Coverage
- 401(k)
- Additional performance-based incentives
REQUIREMENTS
- Strong experience administering High Performance Computing (HPC) environments
- Experience with AI cluster administration and infrastructure operations
- Hands-on Kubernetes administration experience in on-premises environments
- Experience provisioning and managing PV/PVC storage through Kubernetes CSI drivers
- Strong Linux administration skills, specifically Ubuntu
- Scripting experience with Bash and/or Python
- Proven troubleshooting and operational support experience
- Ability to manage and maintain production infrastructure environments
Experience With One Or More Of The Following
- Dell PowerScale/Isilon
- VAST Storage
- NetApp ONTAP
- DDN IntelliFlash
- DDN Exascaler
- Lustre Parallel File Systems
Successful Candidates May Come From Organizations Focused On
- AI Infrastructure
- Machine Learning Platforms
- HPC Operations
- Research Computing
- Biotechnology
- Academic Medical Centers
- Digital Biology
- Financial Services AI Platforms
- Automotive AI Initiatives
- Large-Scale Data Science Environments
PREFERRED
- NVIDIA ecosystem experience
- NVIDIA Base Command Manager (BCM)
- Bright Cluster Manager
- MLOps platform exposure
- Containerization technologies and orchestration platforms
- High-performance networking experience
- RDMA technologies
- InfiniBand networking
- NVIDIA UFM
- Parallel file system administration
- Storage Technologies (highly desired)
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future. We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law. This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
By clicking “Apply Today” you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.
INTRODUCTION
Kforce has a client in Austin, TX that is seeking a Machine Learning & AI Infrastructure Engineer. This is not a traditional AI Engineer or Data Scientist role. The hiring team is specifically seeking a unique blend of: HPC Administrator + Kubernetes Administrator + AI Infrastructure Operations Engineer. Candidates who have owned, operated, supported, and troubleshot production AI or HPC environments will be the strongest fit. Experience administering and maintaining systems is significantly more important than architecture-only experience.
Responsibilities
- Administer and support AI and HPC cluster environments
- Manage day-to-day operations of large-scale compute infrastructure
- Deploy, maintain, and troubleshoot Kubernetes-based platforms
- Ensure reliability, performance, and scalability across compute, storage, and networking environments
- Support AI model training and inference infrastructure
- Automate operational processes through scripting and tooling
- Partner with engineering teams and customers to optimize platform performance
- Troubleshoot complex infrastructure, networking, storage, and containerization issues
- Support both internal platforms and customer-facing environments
Why Consider This Opportunity?
- 100% Remote Environment
- Exposure to cutting-edge AI, GenAI, and HPC technologies
- Flat organizational structure with minimal bureaucracy
- Direct impact on strategic technology initiatives
- Opportunity to work on platforms that support healthcare, research, drug discovery, and other meaningful AI-driven innovations
- High visibility and collaboration with industry-leading technical teams
COMPENSATION & BENEFITS
- Base Salary: $175,000 - $200,000+
- Annual Bonus: Typically 10%-15%
- Medical, Dental, and Vision Coverage
- 401(k)
- Additional performance-based incentives
REQUIREMENTS
- Strong experience administering High Performance Computing (HPC) environments
- Experience with AI cluster administration and infrastructure operations
- Hands-on Kubernetes administration experience in on-premises environments
- Experience provisioning and managing PV/PVC storage through Kubernetes CSI drivers
- Strong Linux administration skills, specifically Ubuntu
- Scripting experience with Bash and/or Python
- Proven troubleshooting and operational support experience
- Ability to manage and maintain production infrastructure environments
Experience With One Or More Of The Following
- Dell PowerScale/Isilon
- VAST Storage
- NetApp ONTAP
- DDN IntelliFlash
- DDN Exascaler
- Lustre Parallel File Systems
Successful Candidates May Come From Organizations Focused On
- AI Infrastructure
- Machine Learning Platforms
- HPC Operations
- Research Computing
- Biotechnology
- Academic Medical Centers
- Digital Biology
- Financial Services AI Platforms
- Automotive AI Initiatives
- Large-Scale Data Science Environments
PREFERRED
- NVIDIA ecosystem experience
- NVIDIA Base Command Manager (BCM)
- Bright Cluster Manager
- MLOps platform exposure
- Containerization technologies and orchestration platforms
- High-performance networking experience
- RDMA technologies
- InfiniBand networking
- NVIDIA UFM
- Parallel file system administration
- Storage Technologies (highly desired)
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future. We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law. This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
By clicking “Apply Today” you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.
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Who's Hiring
Top Industries Hiring
- Technology & Software42
- Consulting & Professional Services18
- Automotive10
- Healthcare & Medical Services10
- Staffing & Recruiting9
What Employers Look For
The qualifications that appear most often in remote machine learning jobs.
- Proficiency in Python and at least one major 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 cloud platforms such as AWS, GCP, or Azure for ML workloads
- Experience with data pipelines, feature engineering, and model evaluation workflows
- Bachelor's or master's degree in computer science, statistics, mathematics, or a related field
Tips for Your Remote Machine Learning Job Search
Build a portfolio that shows async work
Remote machine learning employers want evidence you can work without hand-holding. Document your projects end-to-end on GitHub with clear READMEs, reproducible notebooks, and model cards that explain your decisions. Async-readable documentation is itself a signal you'll thrive on a distributed team.
Demonstrate written communication from the start
Remote ML teams run on written communication, and your application materials are the first test. Write cover letters and follow-ups that are specific, structured, and easy to read quickly. Employers screening remote candidates treat clear written reasoning as a proxy for how you'll collaborate across time zones.
Target remote-first companies explicitly
Remote-first firms and AI-native startups build their processes around distributed teams, making them far more likely to hire and retain remote machine learning engineers long-term. Filter your search for companies with fully remote or distributed-by-design structures rather than legacy employers experimenting with hybrid arrangements.
Apply early to remote roles that fit
Migrate Mate lists remote machine learning openings from across the U.S. in one place, so you can find roles that match your skills and apply directly without sifting through location-filtered results. Applying in the first days a role is listed improves your odds before hiring pipelines fill.
Remote Machine Learning Jobs: Frequently Asked Questions
How do I get a remote machine learning job?
Target companies that already run distributed engineering teams, since they have the infrastructure and culture for remote machine learning work. Remote employers screen hard for self-direction, clear async written communication, and hands-on fluency with ML frameworks like PyTorch or TensorFlow. A public GitHub portfolio with documented experiments, model cards, and reproducible results gives you a concrete edge over candidates who rely on credentials alone.
Which companies hire remote machine learnings?
Employers currently hiring remote machine learnings include Block, CVS Health, and Jobot, per current remote listings on Migrate Mate as of August 2026. Remote-first technology companies, AI-native startups, and distributed teams in finance and healthcare tend to hire for this role across the U.S. without location requirements.
Can you get a remote machine learning job with no experience?
Yes, but remote entry-level machine learning roles are harder to land because employers expect you to work independently from day one without in-person mentorship. AI-native startups and research-focused companies are the most open to junior candidates. A strong public portfolio of end-to-end ML projects, contributions to open-source repositories, and demonstrated async communication skills can open doors that a thin resume alone cannot.
Do you need a degree for remote machine learning jobs?
Not always. Many remote employers weigh demonstrable skills and project results heavily alongside or instead of a formal degree, particularly at startups and AI-product companies. What matters most is evidence you can build, train, evaluate, and deploy models independently. A portfolio showing real ML pipelines, published Kaggle results, or open-source contributions often carries more weight than the credential alone.
Which industries hire the most remote machine learnings?
Remote machine learning roles concentrate in Technology & Software, Consulting & Professional Services, and Automotive, based on current remote listings on Migrate Mate as of August 2026. Those sectors rely on distributed engineering teams that can build and iterate on models without requiring engineers to be in a central office.
See All 251+ Remote Machine Learning Jobs
Find roles that match your experience and apply in just a few clicks.
Find Remote Machine Learning Jobs