Sr. AI Research Engineer

This role is for one of the Weekday's clientsMin Experience: 6 years

Location: USA

JobType: full-time

If you want to own the innovation pipeline, transform research into real-world impact, and build systems unmatched in the market, this is the role for you.

Requirements

What You’Ll Do

• Invent, Implement, Impact – Take cutting-edge advances in LLMs, NLP, OCR, and computer vision, and apply them to messy, multilingual, high-stakes financial documents.
• Own the Model Lifecycle – Lead end-to-end development: data collection and curation, architecture design, training, evaluation, and deployment.
• Benchmark the Best – Design and refine internal evaluation frameworks that set new standards for model quality in financial data extraction.
• Prototype at Speed – Rapidly build and ship experimental features in weeks while maintaining scientific rigor.
• Collaborate with Firepower – Work closely with product, infrastructure, and leadership teams to scale innovations into production systems for global financial use cases.

What We’Re Looking For

Must-Have Firepower

• Paper-to-Prototype Speed – Ability to translate new research into working prototypes within days, not months.
• Code Fluency – Strong Python skills with deep learning frameworks (PyTorch preferred); comfortable debugging and productionizing your own work.
• Model Mastery – Proven experience training and optimizing large models for NLP, computer vision, or multimodal tasks.
• Data Grit – Skilled at handling messy, real-world datasets, not just curated academic benchmarks.
• Problem Ownership – End-to-end problem solver who thrives on responsibility, not just isolated pipeline tasks.

Nice-To-Haves (Differentiators)

• Experience with LLMs, prompt engineering, RAG, or domain adaptation.
• Background in Document AI, OCR, or table understanding.
• Research publications or open-source contributions in AI/ML.
• Experience with distributed training, large-scale inference optimization, or MLOps.

Why This Role Is A Career Accelerator

• Immediate Impact – See your research deployed to production within weeks.
• Ownership – Drive projects from inception to deployment with no silos.
• Velocity – Move faster than big-tech labs while maintaining research excellence.
• Visibility – Work directly with senior leadership and decision-makers.
• Legacy – Help shape the technical foundation of a next-generation AI platform.

Skills

• AI Engineering
• Applied Research
• Deep Learning (NLP, CV, Multimodal)
• Python & PyTorch