Machine Learning Engineer Jobs at Anthropic with Visa Sponsorship
Machine Learning Engineer jobs at Anthropic involve working at the frontier of AI safety research and large-scale model development. The company sponsors H-1B visa, H-1B1 visa, and E-3 visas for this function, reflecting a consistent commitment to hiring international talent for highly specialized technical roles.
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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
Anthropic’s performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training. As an Engineering Manager on these teams you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems. You also will help bring clarity, focus, and context to your teams in a fast paced, dynamic environment.
Responsibilities
- Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems
- Become familiar with the team’s technical stack enough to make targeted contributions as an individual contributor
- Manage day-to-day execution of the team's work
- Prioritize the team’s work and manage projects in a highly dynamic, fast paced environment
- Coach and support your reports in understanding, and pursuing, their professional growth
- Maintain a deep understanding of the team's technical work and its implications for AI safety
You May Be a Good Fit If You
- Have 1+ years of management experience in a technical environment, particularly performance or distributed systems
- Have a background in machine learning, AI, or a similar related technical field
- Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
- Excel at building strong relationships with stakeholders at all levels
- Are a quick learner, capable of understanding and contributing to discussions on complex technical topics
- Have experience managing teams through periods of rapid growth and change
- Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level of abstraction) to be effective
Strong Candidates May Also Have Experience With
- High performance, large-scale ML systems
- GPU/Accelerator programming
- ML framework internals
- OS internals
- Language modeling with transformers
The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary
$500,000—$850,000 USD
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
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.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
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
Anthropic’s performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training. As an Engineering Manager on these teams you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems. You also will help bring clarity, focus, and context to your teams in a fast paced, dynamic environment.
Responsibilities
- Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems
- Become familiar with the team’s technical stack enough to make targeted contributions as an individual contributor
- Manage day-to-day execution of the team's work
- Prioritize the team’s work and manage projects in a highly dynamic, fast paced environment
- Coach and support your reports in understanding, and pursuing, their professional growth
- Maintain a deep understanding of the team's technical work and its implications for AI safety
You May Be a Good Fit If You
- Have 1+ years of management experience in a technical environment, particularly performance or distributed systems
- Have a background in machine learning, AI, or a similar related technical field
- Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
- Excel at building strong relationships with stakeholders at all levels
- Are a quick learner, capable of understanding and contributing to discussions on complex technical topics
- Have experience managing teams through periods of rapid growth and change
- Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level of abstraction) to be effective
Strong Candidates May Also Have Experience With
- High performance, large-scale ML systems
- GPU/Accelerator programming
- ML framework internals
- OS internals
- Language modeling with transformers
The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary
$500,000—$850,000 USD
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
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.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
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 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 JobsTips for Finding Machine Learning Engineer Jobs at Anthropic
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 visa, 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.
Frequently 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 visa, 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 visa 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.