Machine Learning Research Engineer - New Grad

2 Months ago • All levels

About the job

Job Description

Scale is seeking a Machine Learning Research Engineer with a PhD and strong LLM experience. You'll develop ML solutions for human-in-the-loop systems, improve data quality, advance LLMs, and deploy models in production. Experience in research, deep learning frameworks, and publications is a plus.
Must have:
  • PhD Machine Learning
  • LLM Experience
  • Strong Communication
  • Python Programming
Good to have:
  • ML Internship
  • Deep Learning
  • Computer Vision
  • Research Experience
Perks:
  • Customer Exposure
  • Research Opportunities
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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 Engineering
  • LLM working experience
  • Strong communication skills, written and verbal

 

Ideally you’d have:

  • Have had a previous internship around Machine Learning, Deep Learning, or Computer Vision
  • Experience as a researcher, including internships, full-time, or at a lab
  • Strong high-level programming skills (e.g., Python) and familiarity with at least one deep learning framework
  • Publications in top-tier journals such as NeurIPS, ICLR, CVPR, AAAI, etc. or contributions to opensource projects
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