Research Engineer / Research Scientist, Tokens

JRNLClub; New York (NY); Hybride; USD 350 000 - 500 000; Plein temps

Avantages offerts par ce poste

Competitive compensation

Equity options

Generous vacation

Parental leave

Flexible working hours

Office space

Résumé du poste

Anthropic is seeking a Research Engineer/Research Scientist to help build large-scale ML systems and contribute to cutting-edge research in a collaborative setting. You will touch code, improve our infrastructure, run experiments, and help scale experiments across teams.

We value safety, steerable AI, and responsible research. This evergreen role welcomes motivated researchers and engineers who want to advance trustworthy AI and its societal impact while enjoying a flexible hybrid work

Qualifications

• Significant software engineering experience.
• Bachelor’s degree or equivalent in a relevant field.
• Interest in machine learning research and its societal impact.
• Ability to work across teams and contribute to interdisciplinary projects.
• Willingness to learn and adapt in a fast-paced environment.

Responsabilités

• Build large-scale ML systems and improve throughput.
• Run and design scientific experiments to validate research ideas.
• Improve dev tooling and infrastructure for research workflows.
• Collaborate with researchers, engineers, policy experts, and product teams.
• Contribute to code quality, scaling, and reliability across the stack.

Connaissances

Software engineering

Results oriented

Pair programming

ML research interest

Societal impact awareness

Kubernetes

PyTorch

Transformers

OS internals

Formation

Bachelor's degree

Outils

Kubernetes

PyTorch

Transformers

OS internals

Description du poste

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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.

You want to build large scale ML systems from the ground up. You care about making safe, steerable, trustworthy systems. As a Research Engineer, you'll touch all parts of our code and infrastructure, whether that's making the cluster more reliable for our big jobs, improving throughput and efficiency, running and designing scientific experiments, or improving our dev tooling. You're excited to write code when you understand the research context and more broadly why it's important.

Note: This is an "evergreen" role that we keep open on an ongoing basis. We receive many applications for this position, and you may not hear back from us directly if we do not currently have an open role on any of our teams that matches your skills and experience. We encourage you to apply despite this, as we are continually evaluating for top talent to join our team. You are also welcome to reapply as you gain more experience, but we suggest only reapplying once per year.

We may also put up separate, team-specificjob postings . In those cases, the teams will give preference to candidates who apply to the team-specific postings, so if you are interested in a specific team please make sure to check for team-specific job postings!

You may be a good fit if you:

• Have significant software engineering experience
• 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 learn more about machine learning research
• Care about the societal impacts of your work

Strong candidates may also have experience with:

• High performance, large-scale ML systems
• GPUs, Kubernetes, Pytorch, or OS internals
• Language modeling with transformers

Representative projects:

• Optimizing the throughput of a new attention mechanism
• Comparing the compute efficiency of two Transformer variants
• Making a Wikipedia dataset in a format models can easily consume
• Scaling a distributed training job to thousands of GPUs
• Writing a design doc for fault tolerance strategies
• Creating an interactive visualization of attention between tokens in a language model

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.

$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.

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 [e-mail] 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—visitanthropic.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 aboutour policy for using AI in our application process.