Machine Learning Engineer, Trust & Safety

Company:  Karkidi
Location: San Francisco
Closing Date: 07/11/2024
Salary: £250 Per Annum
Hours: Full Time
Type: Permanent
Job Requirements / Description

We are looking for ML engineers to help build safety and oversight mechanisms for our AI systems. As a Trust and Safety Machine Learning Engineer, you will work to train models which detect harmful behaviors and help ensure user well-being. You will apply your technical skills to uphold our principles of safety, transparency, and oversight while enforcing our terms of service and acceptable use policies.

About Anthropic

Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our customers and for society as a whole. Our interdisciplinary team has experience across ML, physics, policy, business and product.

Responsibilities:

  1. Build machine learning models to detect unwanted or anomalous behaviors from users and API partners, and integrate them into our production system
  2. Improve our automated detection and enforcement systems as needed
  3. Analyze user reports of inappropriate accounts and build machine learning models to detect similar instances proactively
  4. Surface abuse patterns to our research teams to harden models at the training stage

You may be a good fit if you:

  1. Have 4+ years of experience in a data scientist, research scientist, or research/ML engineering position, preferably with a focus on trust and safety.
  2. Have proficiency in SQL, Python, and data analysis/data mining tools.
  3. Have proficiency in building trust and safety AI/ML systems, such as behavioral classifiers or anomaly detection.
  4. Have strong communication skills and ability to explain complex technical concepts to non-technical stakeholders.
  5. Care about the societal impacts and long-term implications of your work.

Strong candidates may also:

  1. Have experience with machine learning frameworks like Scikit-Learn, Tensorflow, or Pytorch
  2. Have experience with full stack engineering to build internal tooling
  3. Have experience with high performance, large-scale ML systems
  4. Have experience with language modeling with transformers
  5. Have experience with reinforcement learning
  6. Have experience with large-scale ETL

Annual Salary:

The expected salary range for this position is $300k - $450k USD.

Hybrid policy & visa sponsorship:

Currently, we expect all staff to be in our office at least 25% of the time. 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 or United Kingdom, 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 - On top of this position's salary (listed above), 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:

  1. Optional equity donation matching at a 3:1 ratio, up to 50% of your equity grant.
  2. Comprehensive health, dental, and vision insurance for you and all your dependents.
  3. 401(k) plan with 4% matching.
  4. 22 weeks of paid parental leave.
  5. Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more!
  6. Stipends for education, home office improvements, commuting, and wellness.
  7. Fertility benefits via Carrot.
  8. Daily lunches and snacks in our office.
  9. Relocation support for those moving to the Bay Area.

UK Benefits:

  1. Optional equity donation matching at a 3:1 ratio, up to 50% of your equity grant.
  2. Private health, dental, and vision insurance for you and your dependents.
  3. Pension contribution (matching 4% of your salary).
  4. 22 weeks of paid parental leave.
  5. Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more!
  6. Health cash plan.
  7. Life insurance and income protection.
  8. 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. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both as needed.

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.

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