Machine Learning Engineer Jobs at Anthropic with Visa Sponsorship
Anthropic hires Machine Learning Engineers to work at the frontier of AI safety research and large-scale model development. The company sponsors H-1B, H-1B1, and E-3 visas for this function, reflecting a consistent commitment to hiring international talent for highly specialized technical roles.
See All Machine Learning Engineer at Anthropic JobsOverview
Showing 5 of 28+ Machine Learning Engineer Jobs at Anthropic jobs
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
See all 28+ Machine Learning Engineer Jobs at Anthropic
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Engineer Jobs at Anthropic.
Get Access To All JobsAbout Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About The Role
We are looking for ML engineers to help build safety and oversight mechanisms for our AI systems. As a Safeguards Machine Learning Engineer, you will work to train models which detect harmful behaviors and help ensure user well-being. You will apply your technical skills to uphold our principles of safety, transparency, and oversight while enforcing our terms of service and acceptable use policies.
Responsibilities
- Build machine learning models to detect unwanted or anomalous behaviors from users and API partners, and integrate them into our production system
- Improve our automated detection and enforcement systems as needed
- Analyze user reports of inappropriate accounts and build machine learning models to detect similar instances proactively
- Surface abuse patterns to our research teams to harden models at the training stage
You May Be a Good Fit If You
- Have 4+ years of experience in a research/ML engineering or an applied research scientist position, preferably with a focus on AI safety.
- Have proficiency in Python, LLMs, SQL and data analysis/data mining tools.
- Have proficiency in building safe AI/ML systems, such as behavioral classifiers or anomaly detection.
- Have strong communication skills and ability to explain complex technical concepts to non-technical stakeholders.
- Care about the societal impacts and long-term implications of your work.
Strong Candidates May Also Have Experience With
- Machine learning frameworks like Scikit-Learn, TensorFlow, or PyTorch
- High-performance, large-scale ML systems
- Language modeling with transformers
- Reinforcement learning
- Large-scale ETL
The expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.
Annual Salary
$315,000—$425,000 USD
Logistics
Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
How We're Different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About The Role
We are looking for ML engineers to help build safety and oversight mechanisms for our AI systems. As a Safeguards Machine Learning Engineer, you will work to train models which detect harmful behaviors and help ensure user well-being. You will apply your technical skills to uphold our principles of safety, transparency, and oversight while enforcing our terms of service and acceptable use policies.
Responsibilities
- Build machine learning models to detect unwanted or anomalous behaviors from users and API partners, and integrate them into our production system
- Improve our automated detection and enforcement systems as needed
- Analyze user reports of inappropriate accounts and build machine learning models to detect similar instances proactively
- Surface abuse patterns to our research teams to harden models at the training stage
You May Be a Good Fit If You
- Have 4+ years of experience in a research/ML engineering or an applied research scientist position, preferably with a focus on AI safety.
- Have proficiency in Python, LLMs, SQL and data analysis/data mining tools.
- Have proficiency in building safe AI/ML systems, such as behavioral classifiers or anomaly detection.
- Have strong communication skills and ability to explain complex technical concepts to non-technical stakeholders.
- Care about the societal impacts and long-term implications of your work.
Strong Candidates May Also Have Experience With
- Machine learning frameworks like Scikit-Learn, TensorFlow, or PyTorch
- High-performance, large-scale ML systems
- Language modeling with transformers
- Reinforcement learning
- Large-scale ETL
The expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.
Annual Salary
$315,000—$425,000 USD
Logistics
Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
How We're Different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
See all 28+ Machine Learning Engineer at Anthropic jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Engineer at Anthropic roles.
Get Access To All JobsTips for Finding Machine Learning Engineer Jobs at Anthropic Jobs
Align your research to Anthropic's safety focus
Anthropic prioritizes interpretability, alignment, and scalable oversight. Frame your resume and portfolio around work that intersects ML engineering with safety-relevant outcomes, not just model performance benchmarks or product delivery metrics.
Prepare for multi-stage technical evaluation
Anthropic's ML Engineer interviews typically include research discussions alongside systems and coding rounds. Have recent work documented clearly so you can speak to architectural decisions, failure modes, and tradeoffs under direct questioning.
Confirm your visa category with HR before signing
Anthropic sponsors H-1B, H-1B1, and E-3 visas. Your nationality determines which path applies, and each has different filing timelines and employer obligations. Confirm which category Anthropic will file before accepting an offer to avoid surprises during onboarding.
Time your application around the H-1B cap
If you need H-1B sponsorship, USCIS registration opens in March for an October 1 start date. Anthropic's ML Engineering roles are cap-subject unless you're already on a valid H-1B, so a late offer can mean waiting an additional year to start.
Use Migrate Mate to find open roles by visa type
Anthropic posts ML Engineering positions across several specializations at once. Use Migrate Mate to filter open roles by the visa types Anthropic sponsors, so you're targeting positions where your immigration pathway is already confirmed.
Secure strong documentation for specialty occupation evidence
USCIS scrutinizes ML Engineer petitions when the role blends research and engineering. A detailed offer letter specifying degree requirements in a specific technical field and a well-defined job duties description strengthens the specialty occupation argument your employer will need to make.
Machine Learning Engineer at Anthropic jobs are hiring across the US. Find yours.
Find Machine Learning Engineer at Anthropic JobsFrequently Asked Questions
Does Anthropic sponsor H-1B visas for Machine Learning Engineers?
Yes, Anthropic sponsors H-1B visas for Machine Learning Engineers. The company has an active sponsorship track record for this function and files petitions on behalf of international hires in technical roles. If you require H-1B sponsorship, confirm the timeline with your recruiter early, as cap-subject petitions must be filed months before your intended start date.
How do I apply for Machine Learning Engineer jobs at Anthropic?
Apply directly through Anthropic's careers page or find open roles filtered by visa sponsorship type on Migrate Mate. Anthropic's ML Engineer hiring process typically includes a recruiter screen, technical assessments covering systems design and ML fundamentals, and research-focused interviews. Tailoring your application to Anthropic's published work on AI safety and interpretability improves your chances of advancing.
Which visa types does Anthropic commonly sponsor for Machine Learning Engineers?
Anthropic sponsors H-1B, H-1B1, and E-3 visas for Machine Learning Engineers. H-1B is available to most nationalities and is the most common path. H-1B1 applies to Chilean and Singaporean nationals, while E-3 is exclusively for Australian citizens. Each category has distinct filing procedures, and your nationality determines which option applies.
What qualifications does Anthropic expect from Machine Learning Engineer candidates?
Anthropic typically expects a graduate degree or equivalent research experience in machine learning, computer science, or a related field. Practical experience with large-scale model training, distributed systems, or ML infrastructure is valued. For visa purposes, your degree field should align closely with the role's duties, as USCIS requires a direct relationship between your academic background and the position.
How do I plan my timeline if I need visa sponsorship to work at Anthropic?
The timeline depends on your visa category. E-3 and H-1B1 petitions can be filed year-round with relatively short processing windows. Cap-subject H-1B petitions require USCIS lottery registration in March, with employment starting no earlier than October 1. If you receive an offer outside that window, discuss whether Anthropic can support a deferred start or premium processing to minimize the gap.
See which Machine Learning Engineer at Anthropic employers are hiring and sponsoring visas right now.
Search Machine Learning Engineer at Anthropic Jobs