Scale works with the industry’s leading foundation model labs to provide high quality data and accelerate progress in machine learning research. As a Machine Learning Research Engineer, you will design next generation data pipelines and supervision strategies in close collaboration with our customers to accelerate progress in Generative AI. The ideal candidate is highly technical and well-versed in recent research progress for LLMs, while also having great communication skills, customer obsession, and passion for evangelizing new research methods. Successful candidates will become true research partners to several top foundation model labs, contributing technically and strategically to the roadmaps for the next generation of large language models.
You will:
- Collaborate closely with researchers from the top foundation model labs to design new strategies and data pipelines involving human supervision
- Partner internally with Scale’s Data Engine team to bring your research and data pipeline ideas to life
- Shape the roadmap for how post-training data is used to supervise the next generation of large language models
- Conduct experiments for new research ideas in post-training, leveraging your unique vantage point as a technical partner to several labs
- Accelerate the meteoric growth of Scale’s Generative AI Data Engine business through deep technical partnership with our customers
Ideally you’d have:
- At least 3 to 5 years of model training and/or deployment experience in a research or production environment
- Strong skills in LLMs and deep learning
- Excellent written and verbal communication skills
- Published research in areas of machine learning at major conferences (NeurIPS, ICML, EMNLP, CVPR, ICLR, etc.) and/or journals
Nice to haves:
- Experience in dealing with large scale AI problems, ideally in the generative-AI field
- Demonstrated expertise in large vision-language models for diverse real-world applications, e.g. detection, question-answering, captioning, etc.
- Strong high-level programming skills (e.g., Python) and familiarity with at least one deep learning framework
- Previous experience in a customer facing role
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 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.
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