# Applied AI Research Engineer

**Company:** [Granica](https://hotfix.jobs/companies/granica)
**Location:** Mountain View, CA
**Role:** ML Engineering
**Skills:** PyTorch, JAX, Python, CUDA, C++, Rust, Distributed Training, Ml Pipelines, Representation Learning, Probabilistic Modeling
**Posted:** 2026-07-08

> Research Engineer building scalable ML systems and pipelines for Large Tabular Models on enterprise structured data. Implement algorithms, optimize training/inference, develop benchmarks, and translate research ideas (led by Stanford Prof. Andrea Montanari) into production.

## Job Description

## What You'll Work On
- Build scalable training, evaluation, and inference pipelines for machine learning systems.
- Implement and optimize algorithms for structured and tabular data.
- Develop benchmarks, datasets, and evaluation frameworks for new research ideas.
- Improve training efficiency, memory usage, and inference performance.
- Prototype new ML systems and rapidly validate research ideas.
- Collaborate closely with Prof. Andrea Montanari and Granica's research team to translate research into production systems.

## What We're Looking For
- BS, MS, or PhD in Computer Science, Machine Learning, Mathematics, or a related field.
- Strong software engineering and machine learning fundamentals.
- Experience building production ML systems or ML infrastructure.
- Hands-on experience with PyTorch or JAX.
- Strong programming skills in Python.
- Experience developing evaluation frameworks, ML pipelines, or distributed systems.
- Ability to translate research ideas into reliable, production-quality software.
- Experience with representation learning, structured or tabular data, probabilistic modeling, distributed training, or ML systems optimization is particularly relevant.

## Bonus
- Experience working closely with research teams.
- Experience optimizing training or inference at scale.
- Experience with CUDA, C++, or Rust.
- Contributions to open-source ML systems.
- Publications or research experience in machine learning.

## Compensation & Benefits
- Competitive salary, meaningful equity, and performance bonus for top performers.
- 401(k) with company match, comprehensive health coverage, and unlimited PTO.
- Daily catered meals in our Mountain View office.
- Support for research, publication, and conference participation.

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