Research Scientist – Tabular & Structured Machine Learning
Conduct research and build foundational ML models for structured and tabular data, combining statistical learning theory, probabilistic modeling, and large-scale systems. Requires a PhD and strong experience in tabular/relational ML.
About the job
What You’ll Build and Research
- Invent and prototype algorithms that advance the foundations of machine learning for structured and tabular data
- Develop new representation learning techniques and information models for large enterprise datasets
- Build adaptive learners combining statistical learning theory, probabilistic modeling, and large-scale systems optimization
- Contribute to the development of large tabular models and structured foundation models
- Design architectures integrating relational, symbolic, and neural learning components
- Research and implement methods for dataset compression, selection, and representation to improve learning efficiency
- Develop cost models and optimization frameworks for large-scale structured learning systems
- Collaborate closely with the Granica research group led by Prof. Andrea Montanari (Stanford) and with systems engineers
- Rapidly prototype new algorithms and evaluate them on real enterprise datasets
- Publish and contribute to the broader research community shaping the future of structured AI and efficient ML systems
What You’ll Bring
- PhD in Machine Learning, Statistics, Computer Science, Applied Mathematics, or a related field
- Research experience related to structured, relational, or tabular data
- Experience in one or more of the following areas:
- Tabular or relational machine learning
- Representation learning for structured data
- Statistical learning theory or generalization
- Probabilistic modeling or Bayesian inference
- Optimization for machine learning
- Scalable or distributed ML systems
- Experience working with structured datasets or relational data systems
- Strong grounding in statistics, optimization, information theory, or probabilistic inference
- Hands-on experience with PyTorch, JAX, or TensorFlow
- Strong programming skills in Python or Rust
- Demonstrated ability to translate theoretical ideas into working systems or prototypes
- Curiosity about how structure and relational information enable new forms of learning and reasoning
- A pragmatic research mindset: you value elegant ideas but also ship systems that work at scale
Bonus
- Research in tabular machine learning, relational representation learning, or structured data modeling
- Experience building large-scale ML infrastructure or distributed training systems
- Familiarity with data systems, query engines, or dataset optimization pipelines
- Publications at top venues such as NeurIPS, ICML, ICLR, COLT, KDD, AAAI
- Contributions to open-source ML systems or research-to-production tooling
Compensation & Benefits
- Competitive salary, meaningful equity, and substantial bonus for top performers
- Flexible time off plus comprehensive health coverage for you and your family
- Support for research, publication, and deep technical exploration
Skills
Machine Learning, PyTorch, JAX, TensorFlow, Python, Rust, Tabular Machine Learning, Representation Learning, Probabilistic Modeling, Statistical Learning Theory
Similar jobs
AI Research jobs
Applied Intuition
Sunnyvale, CA
Research Engineer developing and deploying machine-learning algorithms for autonomous driving and robotics systems. The role targets recent MS or PhD graduates with experience in areas such as foundation models, diffusion policies, reinforcement learning, computer vision, and robotics.
Fireworks AI
San Mateo, CAConduct foundational research on LLMs and multimodal systems, designing architectures and training methods and helping move prototypes into production. The role targets PhD researchers graduating by December 2026 with strong machine-learning research and programming experience.
Perplexity
San Francisco, CABuild and evolve the agent harness powering Perplexity’s flagship answer experience, improving orchestration, context management, performance, reliability, observability, and evaluation. The role requires strong software engineering skills, Python proficiency, and experience shipping large-scale AI systems.
GrayMatter Robotics
Los Angeles, CA
Conduct research and develop foundation models for robotic manipulation and high-precision manufacturing, taking projects from data curation through deployment on industrial robots. The role requires current PhD study, strong Python and deep learning expertise, robotics simulation experience, and research in foundation models.
OnePay
United States
AI Research Intern researching agentic AI applications for customer-facing products and developing working prototypes. The role requires current pursuit of a technical bachelor's degree, prior software engineering or substantial project experience, and interest in LLMs or generative AI.