Tbwa Chiat/Day Inc
Machine Learning Research Engineer - New Grad
Tbwa Chiat/Day 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. Working at Scale will give you opportunities to work with our wide customer base which includes leading research teams and exposure to a wide range of problems within machine learning.We are building a large hybrid human-machine system in service of ML pipelines for dozens of industry-leading customers. Our machine learning models form the basis for Scale’s expansion and future product strategy. We currently complete billions of tasks a month, and will continue to grow to support more complex use cases and more advanced ML powered products.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 projectsPlease 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:$180,000 - $210,000 USD
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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. Working at Scale will give you opportunities to work with our wide customer base which includes leading research teams and exposure to a wide range of problems within machine learning.We are building a large hybrid human-machine system in service of ML pipelines for dozens of industry-leading customers. Our machine learning models form the basis for Scale’s expansion and future product strategy. We currently complete billions of tasks a month, and will continue to grow to support more complex use cases and more advanced ML powered products.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 projectsPlease 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:$180,000 - $210,000 USD
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