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Machine Learning Research Engineer, GenAI Applied ML
Machine Learning Research Engineer, GenAI Applied MLScale AI • San Francisco, CA, United States
Machine Learning Research Engineer, GenAI Applied ML

Machine Learning Research Engineer, GenAI Applied ML

Scale AI • San Francisco, CA, United States
8 hours ago
Job type
  • Full-time
Job description

About Scale

At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including : generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.

About This Role

This role will lead the development of trust & safety models to detect fraud & violations on our platform at large scale. The ideal candidate will have experience in industry working on trust & safety to detect misuse via account and behavioral signals. Successful candidates will be impact oriented, have strong foundations in machine learning, and experience in deploying ML services to production. This position requires not only expertise in classical machine learning but familiarity with neural networks and large language models, along with strong intuitions in regards to testing detection systems in the presence of extreme class imbalance. You will contribute to the future of AI by ensuring we deliver high quality data to leading foundation model builders by ensuring that the contributors on our platform are trustworthy and high quality.

Ideally you’d have :

  • Practical experience deploying machine learning models to production in a microservices cloud environment.
  • Familiarity with LLMs and proficiency in frameworks like scikit-learn, Pytorch, Jax, or Tensorflow. You should also be adept at interpreting research literature and quickly turning new ideas into prototypes.
  • At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.
  • Strong written and verbal communication skills and the ability to operate cross-functionally.
  • Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.

Nice to have :

  • Hands‑on production experience developing models for detecting trust & safety violations.
  • A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.).
  • Hands‑on experience with open source LLM fine‑tuning or involvement in bespoke LLM fine‑tuning projects using Pytorch / Jax.
  • Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to : Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

    Please reference the job posting's subtitle for where this position will be located.

    For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is :

    $176,000 – $220,000 USD

    PLEASE NOTE : Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

    About Us :

    At Scale, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how organizations build and deploy AI. Our products power the world's most advanced LLMs, generative models, and computer vision models. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture. We are expanding our team to accelerate the development of AI applications.

    We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an affirmative action employer and inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

    We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and / or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.

    We comply with the United States Department of Labor's Pay Transparency provision.

    We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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    Machine Learning Research Engineer • San Francisco, CA, United States

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