Software Engineer, Machine Learning Infrastructure
Job description not found
Location: Redwood City
Salary range: None - None
DatologyAI's Posts (76)
Research Scientist, Post-Training
About the CompanyCompanies want to train their own large models on their own data. The current industry standard is to train on a random sample of your data, which is inefficient at best and actively harmful to model quality at worst. There is compelling research showing that smarter data selection can train better models faster—we know because we did much of this research. Given the high costs of training, this presents a huge market opportunity. We founded DatologyAI to translate this research into tools that enable enterprise customers to identify the right data on which to train, resulting in better models for cheaper. Our team has pioneered deep learning data research, built startups, and created tools for enterprise ML. For more details, check out our recent blog posts sharing our high-level results fortext modelsandimage-text models.We've raised over $57M in funding from top investors like Radical Ventures, Amplify Partners, Felicis, Microsoft, Amazon, and notable angels like Jeff Dean, Geoff Hinton, Yann LeCun and Elad Gil. We're rapidly scaling our team and computing resources to revolutionize data curation across modalities.This role is based in Redwood City, CA. We are in office 4 days a week.About the RoleWe’re looking for a Research Scientist to lead work on post-training data curation for foundation models. You’ll design and implement algorithms to generate and improve instruction, preference, and other post-training datasets. You’ll also help bridge the gap between pre-training and post-training by exploring how to jointly optimize data across stages. This role requires strong scientific judgment, fluency with the deep learning literature, and a drive to turn research ideas into real-world impact. You’ll work autonomously, collaborate closely with engineers and product teams, and shape the future of data curation at DatologyAI.What You'll Work OnPost-training data curation.You’ll conduct research on how to algorithmically curate post-training data—e.g., how to generate and refine preference and instruction-following data, how to curate capability- and domain-specific data, and make post-training more effective, controllable, and generalizable.Unifying pre-training and post-training data curation.Pushing the bounds on model capabilities requires unifying post-training and pre-training data curation. You will pursue research on end-to-end data curation: how to curate pre-training data to improve the post-trainability of models and how to jointly optimize pre- and post-training data curation, all in service of maximizing the final performance of post-trained models.Transform messy literature into practical improvements.The research literature is vast, rife with ambiguity, and constantly evolving. You will use your skills as a scientist to source, vet, implement, and improve promising ideas from the literature and of your own creation.Conduct science driven by real-world needs.At DatologyAI, we understand that conference reviewers and academic benchmarks don’t always incentivize the most impactful research. Your research will be guided by concrete customer needs and product improvements.How You'll WorkNobody knows how to do your work better than you.We believe that scientists do their best work when they have the autonomy to pursue problems in the manner they prefer, and we will ensure that you are equipped with the context and resources you need to succeed.Science is more than just experiments.We expect our Research Scientists to collaborate closely with engineers, talk to customers, and shape the product vision.About You3+ years of deep learning research experienceExperience with post-training large vision, language, and multimodal modelsPost-training algorithm development, data curation, and/or synthetic data methods for:Preference-based tuning (e.g. DPO, RLVR, RRHF)Alternative supervision & self-supervision techniques such as self-training and chain-of-thought distillationSFT (e.g. instruction tuning and demonstration fine-tuning)Post-training tooling development and engineering experienceStrong understanding of the fundamentals of deep learningSufficient software engineering + deep learning framework (PyTorch or a willingness to learn PyTorch) skills to conduct large-scale research experiments and build production prototypes.Demonstrated track record of success in deep learning research, whether papers, tools, or other research artifacts.We would love it if candidates have:Experience with data management and distributed data processing solutions (e.g. Spark, Snowflake, etc.)Experience building + shipping ML productsCandidates do not need a PhD or extensive publications. Some of the best researchers we’ve worked with have no formal training in machine learning, and obtained all of their experience by working in industry and building products. We believe that adaptability, combined with exceptional communication and collaboration skills are the most important ingredients for successful research in a startup environment.CompensationAt DatologyAI, we are dedicated to rewarding talent with highly competitive salary and significant equity. The salary for this position ranges from $180,000 to $260,000.The candidate's starting pay will be determined based on job-related skills, experience, qualifications, and interview performance.We offer a comprehensive benefits package to support our employees' well-being and professional growth:100% covered health benefits (medical, vision, and dental).401(k) plan with a generous 4% company match.Unlimited PTO policyAnnual $2,000 wellness stipend.Annual $1,000 learning and development stipend.Daily lunches and snacks are provided in our office!Relocation assistance for employees moving to the Bay Area.
Location: Redwood City
Salary range: None - None
Software Engineer, Machine Learning Infrastructure
About the CompanyCompanies want to train their own large models on their own data. The current industry standard is to train on a random sample of your data, which is inefficient at best and actively harmful to model quality at worst. There is compelling research showing that smarter data selection can train better models faster—we know because we did much of this research. Given the high costs of training, this presents a huge market opportunity. We founded DatologyAI to translate this research into tools that enable enterprise customers to identify the right data on which to train, resulting in better models for cheaper. Our team has pioneered deep learning data research, built startups, and created tools for enterprise ML. For more details, check out our recent blog posts sharing our high-level results fortext modelsandimage-text models.We've raised over $57M in funding from top investors like Radical Ventures, Amplify Partners, Felicis, Microsoft, Amazon, and notable angels like Jeff Dean, Geoff Hinton, Yann LeCun and Elad Gil. We're rapidly scaling our team and computing resources to revolutionize data curation across modalities.This role is based in Redwood City, CA. We are in office 4 days a week.About the RoleWe’re looking for seasoned ML Infrastructure engineers with experience designing, building, and maintaining training infrastructure for our in-house ML research and validation efforts and the core infrastructure for running the curation pipeline that we deliver to our customers. As one of our early senior hires, you will partner closely with our founders on the direction of our product and drive business-critical technical decisions.You will contribute to developing core infrastructure components that impact our ability to deliver, scale, and deploy our product. These are key components of our stack that allow us to process customer data and apply state-of-the-art research to identify the most informative data points in large-scale datasets. You will have a broad impact on the technology, product, and our company's culture.What You'll Work OnArchitect, build and maintain the infrastructure that ensures highly available GPU workloads for training-purposesTroubleshoot and resolve issues across GPU resources, networking, OS, drivers, and cloud environments, automate detection and recovery of such issuesDesign, build, and maintain the infrastructure that powers our data curation product.Partner with researchers and engineers to bring new features and research capabilities to our customersEnsure that our infrastructure and systems are reliable, secure, and worthy of our customers' trust.About YouThere are a few specific things we’ll be looking for that will help you succeed in this role:5+ years of experienceHave meaningful experience with leading and building production ML infrastructure and platforms that deliver on major product initiatives.Proficiency in Python and in the most commonly used tools in the infrastructure space: Linux, Kubernetes, Terraform / Pulumi, etcStrong knowledge of hardening cloud native and especially K8s workloads.Experience maintaining a high-quality bar for design, correctness, and testing.Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeedOwn problems end-to-end and are willing to pick up whatever knowledge you're missing to get the job done.Experience running data-processing workloads in k8s (e.g spark on k8s)Don’t meet every single requirement?We still encourage you to apply. If you’re excited about our mission and eager to learn, we want to hear from you!CompensationAt DatologyAI, we are dedicated to rewarding talent with highly competitive salary and significant equity. The salary for this position ranges from $180,000 to $250,000.The candidate's starting pay will be determined based on job-related skills, experience, qualifications, and interview performance.We offer a comprehensive benefits package to support our employees' well-being and professional growth:100% covered health benefits (medical, vision, and dental).401(k) plan with a generous 4% company match.Unlimited PTO policyAnnual $2,000 wellness stipend.Annual $1,000 learning and development stipend.Daily lunches and snacks are provided in our office!Relocation assistance for employees moving to the Bay Area.
Location: Redwood City
Salary range: None - None