
Machine Learning Researcher
Kiddom
full-time
Posted on:
Location Type: Hybrid
Location: San Francisco • California • United States
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Salary
💰 $180,000 - $280,000 per year
Job Level
Tech Stack
About the role
- Join our mission to revolutionize K-12 education at the intersection of cutting-edge AI and impactful learning outcomes.
- As a Machine Learning Researcher, you will play a pivotal role in pushing the boundaries of what’s possible with AI in education.
- Your work will assist teachers by personalizing their teaching experience and improving student outcomes.
- This role combines technical excellence with an opportunity to make a tangible impact on the lives of educators and students nationwide.
Requirements
- At least 1+ year working with generative AI models.
- Hands-on experience with generative AI technologies, including prompt engineering, Retrieval-Augmented Generation (RAG), fine-tuning, and evaluation of large language model applications.
- Proficiency in Python programming and version control.
- Strong understanding of the latest AI trends and practices to maintain state-of-the-art solutions.
- Collaboration: Excellent communication skills to work effectively with cross-functional teams.
- Education: PhD or Master's in Computer Science, Data Science, or a related field, or equivalent experience.
Benefits
- Competitive salary
- Meaningful equity
- Health insurance benefits: medical (various PPO/HMO/HSA plans), dental, vision, disability and life insurance
- One Medical membership (in participating locations)
- Flexible vacation time policy (subject to internal approval). Average use 4 weeks off per year.
- 10 paid sick days per year (pro rated depending on start date)
- Paid holidays
- Paid bereavement leave
- Paid family leave after birth/adoption. Minimum of 16 paid weeks for birthing parents, 10 weeks for caretaker parents. Meant to supplement benefits offered by State.
- Commuter and FSA plans
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
generative AI modelsprompt engineeringRetrieval-Augmented Generation (RAG)fine-tuningevaluation of large language model applicationsPython programmingversion controlAI trendsstate-of-the-art solutions
Soft Skills
excellent communication skillscollaboration
Certifications
PhD in Computer ScienceMaster's in Data Science