Location: San Francisco, CA
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:
You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior of powerful AI systems. You care about making AI helpful, honest, and harmless, and are interested in the ways that this could be challenging in the context of human-level capabilities. You could describe yourself as both a scientist and an engineer. As a Research Engineer on Alignment Science, you'll contribute to exploratory experimental research on AI safety, with a focus on risks from powerful future systems (like those we would designate as ASL-3 or ASL-4 under our
Responsible Scaling Policy
), often in collaboration with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team.
Our blog
provides an overview of topics that the Alignment Science team is either currently exploring or has previously explored. Our current topics of focus include...
Scalable Oversight:
Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains.
AI Control:
Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios.
Alignment Stress-testing
:
Creating
model organisms of misalignment
to improve our empirical understanding of how alignment failures might arise.
Automated Alignment Research:
Building and aligning a system that can speed up & improve alignment research.
Alignment Assessments
: Understanding and documenting the highest-stakes and most concerning emerging properties of models through pre-deployment alignment and welfare assessments (see our
Claude 4 System Card
)
, misalignment-risk safety cases, and coordination with third-party evaluators.
Safeguards Research
: Developing robust defenses against adversarial attacks, comprehensive evaluation frameworks for model safety, and automated systems to detect and mitigate potential risks before deployment.
Model Welfare:
Investigating and addressing potential model welfare, moral status, and related questions. See our
program announcement
and welfare assessment in the
Claude 4 system card
for more.
Note: For this role, we conduct all interviews in Python and prefer candidates to be based in the Bay Area.
Representative projects:
Testing the robustness of our safety techniques by training language models to subvert our safety techniques, and seeing how effective they are at subverting our interventions.
Run multi-agent reinforcement learning experiments to test out techniques like
AI Debate
.
Build tooling to efficiently evaluate the effectiveness of novel LLM-generated jailbreaks.
Write scripts and prompts to efficiently produce evaluation questions to test models’ reasoning abilities in safety-relevant contexts.
Contribute ideas, figures, and writing to research papers, blog posts, and talks.
Run experiments that feed into key AI safety efforts at Anthropic, like the design and implementation of our
Responsible Scaling Policy
.
You may be a good fit if you:
Have significant software, ML, or research engineering experience
Have some experience contributing to empirical AI research projects
Have some familiarity with technical AI safety research
Prefer fast-moving collaborative projects to extensive solo efforts
Pick up slack, even if it goes outside your job description
Care about the impacts of AI
Strong candidates may also:
Have experience authoring research papers in machine learning, NLP, or AI safety
Have experience with LLMs
Have experience with reinforcement learning
Have experience with Kubernetes clusters and complex shared codebases
Candidates need not have:
100% of the skills needed to perform the job
Formal certifications or education credentials
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:
$350,000
—
$500,000 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.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
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.
Location: San Francisco, CA | New York City, NY | Seattle, WA
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 production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with.
You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models.
Note: For this role, we conduct all interviews in Python. This role may require responding to incidents on short-notice, including on weekends.
Responsibilities:
Implement and optimize post-training techniques at scale on frontier models
Conduct research to develop and optimize post-training recipes that directly improve production model quality
Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation
Develop tools to measure and improve model performance across various dimensions
Collaborate with research teams to translate emerging techniques into production-ready implementations
Debug complex issues in training pipelines and model behavior
Help establish best practices for reliable, reproducible model post-training
You may be a good fit if you:
Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities
Adapt quickly to changing priorities
Maintain clarity when debugging complex, time-sensitive issues
Have strong software engineering skills with experience building complex ML systems
Are comfortable working with large-scale distributed systems and high-performance computing
Have experience with training, fine-tuning, or evaluating large language models
Can balance research exploration with engineering rigor and operational reliability
Are adept at analyzing and debugging model training processes
Enjoy collaborating across research and engineering disciplines
Can navigate ambiguity and make progress in fast-moving research environments
Strong candidates may also:
Have experience with LLMs
Have a keen interest in AI safety and responsible deployment
We welcome candidates at various experience levels, with a preference for senior engineers who have hands-on experience with frontier AI systems. However, proficiency in Python, deep learning frameworks, and distributed computing is required for this role.
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:
$350,000
—
$500,000 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.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
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.
Location: San Francisco, CA | New York City, NY
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 teams
Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.5 and Opus 4.5. Our work spans several key areas:
Developing systems that enable models to use computers effectively
Advancing code generation through reinforcement learning
Pioneering fundamental RL research for large language models
Building scalable RL infrastructure and training methodologies
Enhancing model reasoning capabilities
We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish.
About the Role
As a Research Engineer within Reinforcement Learning, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to the research direction. You'll work on fundamental research in reinforcement learning, creating 'agentic' models via tool use for open-ended tasks such as computer use and autonomous software generation, improving reasoning abilities in areas such as mathematics, and developing prototypes for internal use, productivity, and evaluation.
Representative projects:
Architect and optimize core reinforcement learning infrastructure, from clean training abstractions to distributed experiment management across GPU clusters. Help scale our systems to handle increasingly complex research workflows.
Design, implement, and test novel training environments, evaluations, and methodologies for reinforcement learning agents which push the state of the art for the next generation of models.
Drive performance improvements across our stack through profiling, optimization, and benchmarking. Implement efficient caching solutions and debug distributed systems to accelerate both training and evaluation workflows.
Collaborate across research and engineering teams to develop automated testing frameworks, design clean APIs, and build scalable infrastructure that accelerates AI research.
You may be a good fit if you:
Are proficient in Python and async/concurrent programming with frameworks like Trio
Have experience with machine learning frameworks (PyTorch, TensorFlow, JAX)
Have industry experience in machine learning research
Can balance research exploration with engineering implementation
Enjoy pair programming (we love to pair!)
Care about code quality, testing, and performance
Have strong systems design and communication skills
Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems
Strong candidates may have:
Familiarity with LLM architectures and training methodologies
Experience with reinforcement learning techniques and environments
Experience with virtualization and sandboxed code execution environments
Experience with Kubernetes
Experience with distributed systems or high-performance computing
Experience with Rust and/or C++
Strong candidates need not have:
Formal certifications or education credentials
Academic research experience or publication history
Deadline to apply:
None. Applications will be reviewed on a rolling basis.
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.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
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.
Location: London, UK
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:
You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior of powerful AI systems. You care about making AI helpful, honest, and harmless, and are interested in the ways that this could be challenging in the context of human-level capabilities. You could describe yourself as both a scientist and an engineer. As a Research Engineer on Alignment Science, you'll contribute to exploratory experimental research on AI safety, with a focus on risks from powerful future systems (like those we would designate as ASL-3 or ASL-4 under our
Responsible Scaling Policy
), often in collaboration with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team.
Our blog
provides an overview of topics that the Alignment Science team is either currently exploring or has previously explored. For the London team, we are opportunistically hiring for the following research areas:
AI Control:
Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios.
Alignment Stress-testing
:
Creating
model organisms of misalignment
to improve our empirical understanding of how alignment failures might arise.
Note: Currently, the team's hub is in San Francisco, so we require all candidates to be based at least 25% in London
and
travel to San Francisco occasionally. Additionally, we are prioritizing growing our San Francisco teams, so you may not hear back on your application to the London team unless we see an unusually strong fit. For this role, we conduct all interviews in Python.
Representative Projects:
Testing the robustness of our safety techniques by training language models to subvert our safety techniques, and seeing how effective they are at subverting our interventions.
Run multi-agent reinforcement learning experiments to test out techniques like
AI Debate
.
Build tooling to efficiently evaluate the effectiveness of novel LLM-generated jailbreaks.
Write scripts and prompts to efficiently produce evaluation questions to test models’ reasoning abilities in safety-relevant contexts.
Contribute ideas, figures, and writing to research papers, blog posts, and talks.
Run experiments that feed into key AI safety efforts at Anthropic, like the design and implementation of our
Responsible Scaling Policy
.
You may be a good fit if you:
Have significant software, ML, or research engineering experience
Have some experience contributing to empirical AI research projects
Have some familiarity with technical AI safety research
Prefer fast-moving collaborative projects to extensive solo efforts
Pick up slack, even if it goes outside your job description
Care about the impacts of AI
Strong candidates may also:
Have experience authoring research papers in machine learning, NLP, or AI safety
Have experience with LLMs
Have experience with reinforcement learning
Have experience with Kubernetes clusters and complex shared codebases
Candidates need not have:
100% of the skills needed to perform the job
Formal certifications or education credentials
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:
£260,000
—
£370,000 GBP
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.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
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.
Location: Bremen, Germany
Our mission
Constructor’s mission is to enable all educational organisations to provide high-quality digital education to 10x people with 10x efficiency.
With strong expertise in machine intelligence and data science, Constructor’s all-in-one platform for education and research addresses today’s pressing educational challenges: access inequality, tech clutter, and low engagement of students.
Please send your resume in English only.
Interns are NOT eligible for equipment and other benefits as the position is temporary.
The Reality
The frontier models are converging into commodities; the engine is no longer the differentiator. The scarcity in 2026 is not the model.
We are not looking for people to fine-tune Llama on toy datasets or write "better prompts." We are building the runtime systems that turn probabilistic token generation into reliable workers that finish 50-step tasks without spiraling. We are solving the math of multi-step reliability through engineering, not wishful thinking.
What You Will Solve
You will work on the
Agentic Harness
, treating the LLM as a component within a larger, deterministic control system. Your research will focus on:
Architecting loops that survive error accumulation. You will build verification layers that force the agent to recognize its own hallucinations and self-correct.
You will implement systems where the agent compiles its own constraints and the harness enforces them via constrained decoding or external execution.
You will optimise KV-cache hit rates and design "restorable compression" strategies to prevent attention decay.
Who We Are Looking For
We are looking for
systems thinkers
who happen to know ML, not the other way around.
You know that a demo is not a product. You are interested in the "boring" engineering: state machines, retries, idempotency, serialisation — that actually makes agents work.
You are comfortable working with the raw output of the model and building robust software in Python or Rust around it.
You understand why dynamic tool loading destroys inference economics. You prefer deterministic guardrails over "prompting it to be nicer."
You are willing to read a 500-line trace of a failed agent loop to find the exact moment the context drifted. You care about the "last mile" of reliability.
What We Offer For Interns:
Internship Duration: from 2 months or more
Type of internship:
100% remote
or hybrid
in the office in Bremen (GER), Sofia (BG), Belgrade (SRB), Istanbul (TR), Sakarya (TR), Singapore (SGD)
What We Offer
💻 Choice of work equipment (e.g., laptop, monitor, etc.)
🇬🇧 English classes (iTalki – $130 monthly)
⏰ Flexible schedule (we usually work between 09:00/10:00 and 18:00/19:00)
👶 Newborn bonus (€500 per child)
🧠 Patent remuneration
🌴 Paid leave
🧑💻 Remote work in locations without our offices
Hybrid work in locations with offices (2 days in-office, 3 days remote)
Constructor
fosters equal opportunity for people of all backgrounds and identities. We are led by a gender-balanced board committed to building a diverse and inclusive organisation where everyone can become their best self. We do not discriminate based on age, disability, gender identity, sexual orientation, ethnicity, race, religion or belief, parental and family status, or other protected characteristics. We welcome applications from women, men and non-binary candidates of all ethnicities and socio-economic backgrounds. We encourage people belonging to underrepresented groups to apply.
Location: Bremen, Germany
Our mission
Constructor’s mission is to enable all educational organisations to provide high-quality digital education to 10x people with 10x efficiency.
With strong expertise in machine intelligence and data science, Constructor’s all-in-one platform for education and research addresses today’s pressing educational challenges: access inequality, tech clutter, and low engagement of students.
Please send your resume in English only.
Interns are NOT eligible for equipment and other benefits as the position is temporary.
Internship Opportunity at the Research Unit of Constructor Technology in Partnership with the Observatory of Higher Education Innovations at Constructor University
Overview:
The Research Unit of Constructor Technology in Partnership with the Observatory of Higher Education Innovations at Constructor University is looking for a motivated student intern who is passionate about educational technologies and their applications. The ideal candidate is a second or third-year student with a strong interest in research, data analysis, and the EdTech industry. This internship offers valuable learning opportunities, mentorship, and hands-on experience in a dynamic field.
Key Responsibilities:
Assist in analyzing existing EdTech solutions, including platform and infrastructure software, as well as products aimed at end-users such as students, teachers, and administrative staff.
Help investigate and assess the latest trends and innovations in the application of artificial intelligence in education.
Collaborate with team members and researchers to explore tools that enhance productivity and optimize routine tasks.
Proactively participate in a weekly work-group seminar where we discuss findings.
Support the market analysis efforts, including studying economic indicators and trends to identify potential opportunities for the company's development in the EdTech sector.
Participate in external EdTech and education-related activities and share insights with the entire team.
Requirements:
Currently enrolled in a second or third year of a bachelor's program in information technology, economics, or a related field.
Basic understanding of market research and data analysis, with coursework or projects in a related area.
Strong analytical skills, with the ability to work with information and learn to make informed decisions.
Good communication skills and the ability to work effectively within a team.
Enthusiasm for learning and contributing to the field of educational technology.
What Constructor Technology Offers:
A position in a leading company in the EdTech field, actively using innovations to transform education.
Hands-on experience and learning opportunities in market analysis and data-driven decision-making.
Flexible working hours with an expected duration of 6 months, with the possibility of extension based on performance and company needs.
If you are a student with a passion for data, analytics, and educational innovations, we look forward to having you on our team!
What We Offer
💻 Choice of work equipment (e.g., laptop, monitor, etc.)
🇬🇧 English classes (iTalki – $130 monthly)
⏰ Flexible schedule (we usually work between 09:00/10:00 and 18:00/19:00)
👶 Newborn bonus (€500 per child)
🧠 Patent remuneration
🌴 Paid leave
🧑💻 Remote work in locations without our offices
Hybrid work in locations with offices (2 days in-office, 3 days remote)
Constructor
fosters equal opportunity for people of all backgrounds and identities. We are led by a gender-balanced board committed to building a diverse and inclusive organisation where everyone can become their best self. We do not discriminate based on age, disability, gender identity, sexual orientation, ethnicity, race, religion or belief, parental and family status, or other protected characteristics. We welcome applications from women, men and non-binary candidates of all ethnicities and socio-economic backgrounds. We encourage people belonging to underrepresented groups to apply.
Location: Remote
Workplace: Remote
We are building AI to simulate the world through merging art and science.
We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world.
World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached.
Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you.
*Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers.
ABOUT THE ROLE
Building general world models — systems that understand and simulate reality across tasks, modalities, and domains — demands training data that is as rich and varied as the real world itself. We’re looking for Research Engineers to own the data behind our models: what they learn from, how well they learn it, and what new capabilities that unlocks. You will design datasets, run modeling experiments, and build the infrastructure to generate and curate data at scale — directly shaping what our models can do, with applications ranging from creative tools to robotics.
WHAT YOU'LL DO
- Design multimodal, multitask datasets that teach world models new capabilities — deciding what data to collect, generate, or curate and measuring its effect on model behavior
- Run controlled training experiments to understand how data composition drives model performance across tasks and domains
- Build and operate large-scale pipelines for synthetic data generation, filtering, and quality control
- Define evaluations and benchmarks that measure whether our models are actually improving at the things that matter
- Partner with product and creative teams to translate target behaviors and capabilities into concrete data strategies
WHAT YOU'LL NEED
- 4+ years of experience in machine learning, bonus points for data-centric approaches
- Experience with large multimodal datasets and generative models (video, image, or multimodal)
- Deep intuition for how data composition and quality translate to model capabilities
- Comfort working across the full research stack: data analysis, dataset creation, model training, evaluation, and back again
- Proficiency with at least one ML framework (e.g. PyTorch, JAX) and distributed compute tools (e.g. Ray, Kubernetes)
- Excitement about building AI that simulates the world
Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide.
There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range.
Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates.
WORKING AT RUNWAY
Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you.
We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply.
More about Runway
- Universal World Simulator https://runwayml.com/world-simulator.html
- GWM-1 https://runwayml.com/research/introducing-runway-gwm-1
- Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5
- General World Models https://runwayml.com/research/introducing-general-world-models
- Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section
- Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section
- Runway Studios https://runwayml.com/studios
We're excited to be recognized as a best place to work:
Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024
Location: Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY
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 Research Engineers to help us redesign how Claude interacts with external data sources. Many of the paradigms for how data and knowledge bases are organized assume human consumers and constraints. This is no longer true in a world of LLMs! Your job will be to design new architectures for how information is organized, and train language models to optimally use those architectures.
Responsibilities:
Designing and implementing from scratch new information architecture strategies
Performing finetuning and reinforcement learning to teach language models how to interact with new information architectures
Building “hard” knowledge base eval sets to help identify failure modes of how language models work with external data
Designing and evaluating advanced agentic search capabilities.
You may be a good fit if you:
Are a very experienced Python programmer who can quickly produce reliable, high quality code that your teammates love using
Have good machine learning research experience
Have experience developing software that utilizes Large Language Models such as Claude
Are results-oriented, with a bias towards flexibility and impact
Pick up slack, even if it goes outside your job description
Enjoy pair programming (we love to pair!)
Want to partner with world-class ML researchers to develop new LLM capabilities
Care about the societal impacts of your work
Have clear written and verbal communication
Strong candidates will also have experience with:
Collaborating with product teams to quickly prototype and deliver innovative solutions
Building complex agentic systems that utilize LLMs
Developing scalable distributed information retrieval systems, such as search engines, knowledge graphs, RAG, indexing, ranking, query understanding, and distributed data processing
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:
$350,000
—
$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.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
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.
Location: San Francisco, CA | New York City, NY | Seattle, WA
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:
Multi-Agent systems are becoming an increasingly important part of how AI is deployed, whether via fast small-model subagents inside a product, or
large groups of agents
solving
very large problems
. Training Claude to be maximally effective and safe within large groups is a challenging new area of reinforcement learning, and represents a new axis for scaling test time compute.
We are looking for researchers who have experience training multi-agent systems at the largest scale and an appreciation for the incentives and mechanism design that come into play.
Responsibilities:
Help create and optimize environments and data for model training that maximize Claude’s performance or ease of use on agentic tasks
Ideate, develop, and compare the performance of different agent harness configurations (eg memory, context management, communication architectures for agents)
Design and implement rigorous quantitative benchmarks for large scale agentic tasks
Work with our product org to find solutions to our most vexing challenges in applying agents to our products
You may be a good fit if you:
Have experience with large-scale RL on language models
Have experience training multi-agent systems
Enjoy going deeply into the roots of a problem and understanding its foundations, rather than its surface.
Have good communication skills and an interest in working with other researchers on difficult tasks
Have a passion for making powerful technology safe and societally beneficial
Are excited for a mission-driven org with fast-paced, impactful work
Representative projects:
Design and build reinforcement learning environments to train groups of Claudes how to solve problems together efficiently
Design and build agent affordances that unlock new capabilities and scales of agents, while keeping the Bitter Lesson in mind
Design and build a novel eval that measures how large teams of agents interact in groups to solve problems
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.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
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.
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