Scale AI, Inc.
Machine Learning Research Engineer - New Grad EPD San Francisco, CA
Scale AI, Inc., San Francisco, California, United States, 94199
Machine Learning Research Engineer - New Grad
The goal of the ML team at Scale is to develop machine learning solutions advancing the company mission. Our current focus areas are in Generative AI, working on LLMs, post-training, RLHF, safety and capabilities evaluations, scalable alignment, and synthetic data. You’ll be working on a combination of deeply technical ML applications in production and cutting edge research problems.What you’ll do:Research and develop machine learning solutions to assist humans in the loop.Develop systems that improve the creation of high quality ground truth data with speed and accuracy.Research frontier data and post-training methods to advance state of the art LLMs for our customers.Work with public Large Language models to benchmark and make custom versions for internal use cases.Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers.Take models currently in production, identify areas for improvement, improve them using retraining and hyperparameter searches, then deploy without regressing on core model characteristics.Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines.Work with massive datasets to develop both generic models as well as fine tune models for specific products.Required to have:Graduating Fall of 2024 or Spring of 2025 from a PhD with a focus on Machine Learning, Computer Science, Deep Learning, Artificial Intelligence, Electronics EngineeringStrong communication skills, written and verbalIdeally you’d have:Have had a previous internship around Machine Learning, Deep Learning, or Computer VisionExperience as a researcher, including internships, full-time, or at a labStrong high-level programming skills (e.g., Python) and familiarity with at least one deep learning frameworkPublications in top-tier journals such as NeurIPS, ICLR, CVPR, AAAI, etc. or contributions to opensource projectsCompensation:
The base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $180,000 — $210,000 USD.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.
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The goal of the ML team at Scale is to develop machine learning solutions advancing the company mission. Our current focus areas are in Generative AI, working on LLMs, post-training, RLHF, safety and capabilities evaluations, scalable alignment, and synthetic data. You’ll be working on a combination of deeply technical ML applications in production and cutting edge research problems.What you’ll do:Research and develop machine learning solutions to assist humans in the loop.Develop systems that improve the creation of high quality ground truth data with speed and accuracy.Research frontier data and post-training methods to advance state of the art LLMs for our customers.Work with public Large Language models to benchmark and make custom versions for internal use cases.Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers.Take models currently in production, identify areas for improvement, improve them using retraining and hyperparameter searches, then deploy without regressing on core model characteristics.Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines.Work with massive datasets to develop both generic models as well as fine tune models for specific products.Required to have:Graduating Fall of 2024 or Spring of 2025 from a PhD with a focus on Machine Learning, Computer Science, Deep Learning, Artificial Intelligence, Electronics EngineeringStrong communication skills, written and verbalIdeally you’d have:Have had a previous internship around Machine Learning, Deep Learning, or Computer VisionExperience as a researcher, including internships, full-time, or at a labStrong high-level programming skills (e.g., Python) and familiarity with at least one deep learning frameworkPublications in top-tier journals such as NeurIPS, ICLR, CVPR, AAAI, etc. or contributions to opensource projectsCompensation:
The base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $180,000 — $210,000 USD.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.
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