AI ML Engineer Jobs at Anthropic with Visa Sponsorship
AI ML Engineer jobs at Anthropic involve building and aligning frontier AI systems, with roles spanning model training, evaluation, and safety research. The company has an established track record of sponsoring work visas for this function, making it a realistic target for international candidates in machine learning.
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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
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 AI ML Engineer Jobs at Anthropic
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI ML Engineer Jobs at Anthropic.
Get Access To All JobsTips for Finding AI ML Engineer Jobs at Anthropic
Align your portfolio to safety research
Anthropic's AI ML Engineer roles sit at the intersection of capability and alignment. Before applying, reframe your experience around evaluation frameworks, RLHF pipelines, or interpretability work rather than generic ML engineering projects.
Confirm your visa type early
Anthropic sponsors H-1B, H-1B1 visa, and E-3 visas for this role. Knowing which category fits your nationality before your first recruiter screen lets you answer sponsorship questions confidently and avoids delays later in the process.
Target roles that map to specialty occupation criteria
USCIS requires H-1B positions to qualify as specialty occupations. Anthropic's ML Engineer postings typically require a relevant degree in computer science, statistics, or a related field, so ensure your credentials reflect that direct alignment in your application materials.
Prepare for a technical loop that mirrors research interviews
Anthropic's interview process for this function often includes systems design, ML theory, and coding rounds alongside research discussion. Preparing published papers or technical write-ups on model training or evaluation gives you concrete material to reference.
Request a filing timeline during offer negotiation
If you're on OPT, the H-1B cap registration window opens in March and USCIS typically begins accepting petitions October 1. Confirm during the offer stage that Anthropic will file within your remaining work authorization window so there's no gap in status.
Use Migrate Mate to find open roles before they fill
AI ML Engineer positions at Anthropic move quickly. Use Migrate Mate to filter for Anthropic roles that match your visa type so you're applying to openings that are actively accepting sponsored candidates, not listings that have already closed.
Frequently Asked Questions
Does Anthropic sponsor H-1B visas for AI ML Engineers?
Yes, Anthropic sponsors H-1B visas for AI ML Engineer roles. The company participates in the annual H-1B cap registration process, so if you're subject to the cap, your employer needs to register during the March window and petitions become effective October 1. Anthropic also sponsors H-1B1 visa and E-3 visas, which have separate annual allocations and do not require lottery selection.
How do I apply for AI ML Engineer jobs at Anthropic?
Applications go through Anthropic's careers page. Tailor your resume to reflect the specific research or engineering focus of the role, whether that's model training, reinforcement learning from human feedback, or safety evaluation. You can also browse current openings filtered by visa type on Migrate Mate, which surfaces Anthropic roles that are open to sponsored candidates.
Which visa types are commonly used for AI ML Engineer roles at Anthropic?
Anthropic sponsors H-1B, H-1B1 visa, and E-3 visas for this function. H-1B is the most widely used and applies to most nationalities. H-1B1 is available exclusively to Chilean and Singaporean nationals and has a dedicated annual cap. E-3 applies only to Australian citizens and carries its own separate allocation. All three require the role to qualify as a specialty occupation under USCIS definitions.
What qualifications does Anthropic expect for AI ML Engineer roles?
Most postings require a bachelor's degree or higher in computer science, mathematics, or a closely related field, though research-oriented roles often prefer candidates with graduate degrees or published work. Practical experience with large-scale model training, distributed systems, or ML evaluation frameworks is consistently emphasized. Anthropic's alignment focus means experience with RLHF, interpretability, or safety-adjacent research is a meaningful differentiator.
How long does the visa sponsorship process take when joining Anthropic as an AI ML Engineer?
For H-1B transfers from another employer, USCIS generally allows you to begin work upon filing, without waiting for approval. For new H-1B petitions subject to the cap, you need to be selected in the March lottery before the October 1 start date. E-3 and H-1B1 visas are typically processed at a U.S. consulate, with appointment wait times varying by location. Premium processing through USCIS reduces adjudication to 15 business days for eligible petition types.