Research Engineer, GenAI Job at Kiddom (San Francisco)

Job Description

You will be part of Kiddom’s Data Science team, building the foundation of our search, recommendation, and insights systems. Your work will directly support teachers and students by delivering timely insights, personalized content, and intelligent assistance.

Job Responsibility

Architect and scale machine learning systems for search, personalization, and recommendations that power Kiddom’s teacher helper and insight engine
Develop evaluation-first development workflows to measure how models improve teaching efficiency, lesson planning, and student learning outcomes
Fine-tune machine learning models with feedback signals from teachers and students to align outputs with instructional goals and classroom needs
Design intelligent discovery pipelines that combine semantic retrieval, curriculum alignment, and real-time personalization
Build agentic assistants that help teachers plan lessons, adapt instruction, and reduce repetitive tasks
Collaborate closely with product managers, designers, and curriculum experts to translate high-level educational goals into scalable ML-powered systems
Coach and mentor junior ML engineers and data scientists, fostering technical and professional growth

Requirements

5+ years of industry experience applying machine learning to solve real-world problems with large, complex datasets
1–2 years in a technical leadership role
Proven track record designing, evaluating, and deploying ML/AI systems in production environments that drive measurable business impact, ideally in recommendation, personalization, search, or workflow optimization
Strong programming skills in Python
Fluency in data manipulation (SQL, Pandas) and common ML toolkits (scikit-learn, XGBoost, TensorFlow/PyTorch)
Strong analytical skills and ability to break down complex problems into measurable hypotheses and experiments
Excellent communication skills with a history of cross-functional collaboration with product, design, and engineering stakeholders

Nice to have

Deep expertise in modern deep learning frameworks and advanced LLM architectures
Experience building evaluation pipelines for ML/AI systems, ensuring reliable measurement of impact and quality in real-world use
Experience implementing and fine-tuning large language models (LLMs), including prompt engineering, embeddings, and efficient inference optimization
Familiarity with foundation model adaptation techniques such as PEFT, LoRA, or RLHF
Self-motivated innovator who thrives in fast-moving environments and is excited to explore emerging AI techniques to solve meaningful problems in education
Passion for applying cutting-edge AI research to improve teaching workflows and personalize student learning at scale

What we offer

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

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Research Engineer, GenAI

Job Description

Job Responsibility

Requirements

Nice to have

What we offer

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