Research Engineer, Multimodal

DALLAS VA RESEARCH CORPORATION
London
1 week ago
Create job alert
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.

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
  • Reinforcement learning
  • Large-scale ETL
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 expected salary range for this position is:

Annual Salary:
£225,000£340,000 GBP
Logistics

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.

US visa sponsorship:We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate; operations roles are especially difficult to support. But if we make you an offer, we will make every effort to get you into the United States, 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.

Compensation and Benefits*

Anthropic’s compensation package consists of three elements: salary, equity, and benefits. We are committed to pay fairness and aim for these three elements collectively to be highly competitive with market rates.

Equity-For eligible roles, equity will be a major component of the total compensation. We aim to offer higher-than-average equity compensation for a company of our size, and communicate equity amounts at the time of offer issuance.

US Benefits- The following benefits are for our US-based employees:

  • Optional equity donation matching.
  • Comprehensive health, dental, and vision insurance for you and all your dependents.
  • 401(k) plan with 4% matching.
  • 22 weeks of paid parental leave.
  • Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more!
  • Stipends for education, home office improvements, commuting, and wellness.
  • Fertility benefits via Carrot.
  • Daily lunches and snacks in our office.
  • Relocation support for those moving to the Bay Area.

UK Benefits- The following benefits are for our UK-based employees:

  • Optional equity donation matching.
  • Private health, dental, and vision insurance for you and your dependents.
  • Pension contribution (matching 4% of your salary).
  • 21 weeks of paid parental leave.
  • Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more!
  • Health cash plan.
  • Life insurance and income protection.
  • Daily lunches and snacks in our office.

* This compensation and benefits information is based on Anthropic’s good faith estimate for this position as of the date of publication and may be modified in the future.Employees based outside of the UK or US will receive a different benefits package.The level of pay within the range will depend on a variety of job-related factors, including where you place on our internal performance ladders, which is based on factors including past work experience, relevant education, and performance on our interviews or in a work trial.

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.

#J-18808-Ljbffr

Related Jobs

View all jobs

Research Engineer - Chem Bio

Research Engineer / Scientist, Alignment Science (London)

Research Engineer - Data

Research Scientist, Frontier Red Team (Autonomy)

AI Engineer

Machine Learning Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.