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Tech Stack
Tools & technologiesPyTorch
About the role
Key responsibilities & impact- Train, fine-tune, and evaluate ML models and LLMs for real-world government use cases.
- Tackle challenges like OCR, document parsing, and classification to streamline services.
- Source, adapt, and operationalize models from both open-source and vendor ecosystems.
- Enhance automation, reduce manual processes, and boost system performance across the platform.
- Push forward scalable, ethical AI solutions that redefine how people access public support.
Requirements
What you’ll need- 5+ years in machine learning and statistical analysis
- 1+ year working directly with deep learning or LLMs
- Hands-on experience with model training, fine-tuning, and validation for classification/regression tasks (ROC AUC, Precision, Recall, F1)
- Proficiency with frameworks like PyTorch, MLFlow, LightGBM, or similar
- Detail-oriented, rigorous, and adaptable
- Passion for Promise’s work and a commitment to building ethical, transparent AI solutions
- Bonus: Experience in applied AI for fintech, govtech, or other regulated industries.
Benefits
Comp & perks- 100% paid health coverage
- Generous PTO and sick leave
- Lunch, snacks, and coffee provided
- Company retreats
- Opportunities to travel and see the impact of your work
- Hybrid Work: We deeply value in-person collaboration and are in-office or on-site at least four days a week.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningstatistical analysisdeep learningLLMsmodel trainingfine-tuningvalidationclassificationregressionROC AUC
Soft Skills
detail-orientedrigorousadaptablepassion for ethical AIcommitment to transparency