Research Scientist – Post-Training

DatologyAI

. Lead research on post-training data curation for foundation models .

Posted 10/16/2026full-timeSan Mateo • California • United StatesMid-LevelSenior💰 $180,000 - $300,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in deep learning research, particularly in post-training data curation and algorithm development. Proficient in leveraging deep learning frameworks and tools to enhance model performance and product outcomes.

Highest-signal resume keywords

Deep Learning Research ExperiencePost-Training Algorithm DevelopmentData CurationPyTorch SkillsExperience with Preference-Based Tuning

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Deep Learning FundamentalsPost-Training Tooling DevelopmentSynthetic Data MethodsSelf-Supervision TechniquesInstruction TuningDemonstration Fine-TuningData ManagementDistributed Data ProcessingLarge Vision ModelsMultimodal Models

Soft Skills

Autonomous WorkCollaborationCustomer Engagement

Tools & Technologies

PyTorchSparkSnowflake

Industry Keywords

Machine Learning ProductsResearch LiteratureModel PerformanceInstruction-Following DataCapability-Specific Data

Tech Stack

Tools & technologies

PyTorchSpark

About the role

Key responsibilities & impact

Lead research on post-training data curation for foundation models
Design and implement algorithms to generate and improve instruction, preference, and other post-training datasets
Explore jointly optimizing data across pre-training and post-training stages
Curate preference, instruction-following, capability-specific, and domain-specific data
Research end-to-end data curation to improve model post-trainability and final post-trained model performance
Source, vet, implement, and improve promising ideas from research literature and original research
Conduct research guided by customer needs and product improvements
Work autonomously with the context and resources needed to succeed
Collaborate closely with engineers and product teams
Talk to customers and shape product vision

Requirements

What you’ll need

3+ years of deep learning research experience
Experience with post-training large vision, language, and multimodal models
Experience with post-training algorithm development, data curation, and/or synthetic data methods
Experience with preference-based tuning, such as DPO, RLVR, or RRHF
Experience with alternative supervision and self-supervision techniques, such as self-training and chain-of-thought distillation
Experience with SFT, such as instruction tuning and demonstration fine-tuning
Post-training tooling development and engineering experience
Strong understanding of deep learning fundamentals
Software engineering and deep learning framework skills sufficient for large-scale research experiments and production prototypes
PyTorch skills or willingness to learn PyTorch
Demonstrated track record of success in deep learning research through papers, tools, or other research artifacts
Candidates do not need a PhD or extensive publications
Experience with data management and distributed data processing solutions, such as Spark or Snowflake, preferred
Experience building and shipping ML products preferred

Benefits

Comp & perks

100% covered health benefits (medical, vision, and dental)
401(k) plan with a generous 4% company match
Unlimited PTO policy
Paid Parental Leave of 12 weeks
6 months of WFH flexibility
Annual $2,000 wellness stipend
Annual $1,000 learning and development stipend
Daily lunches and snacks provided in the office
Relocation assistance for employees moving to the Bay Area
Meaningful equity