Senior Machine Learning Engineer

Kiddom•San Francisco, CA

About The Position

Kiddom is transforming K–12 education by bringing high-quality curriculum, instructional tools, and student analytics together in one coherent system. We are building Learning Intelligence Technology (LIT), a new category that gives educators the infrastructure to plan, teach, assess, and respond to student needs. With Kiddom, educators spend less time managing administrative burden and more time delivering meaningful student instruction. Kiddom helps schools and districts deliver more equitable, effective, and adaptive learning experiences. We're looking for a seasoned Senior ML Engineer with a track record building production ML systems, ideally in search, recommendation, or personalization, along with some technical leadership experience. You will be part of Kiddom’s AI 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. LLM and fine-tuning experience is a plus, along with genuine interest in applying AI to improve teaching and learning.

Requirements

5+ years of industry experience applying machine learning to solve real-world problems with large, complex datasets, with 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 and 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 Haves

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.
LLM and fine-tuning experience is a plus.
Genuine interest in applying AI to improve teaching and learning.

Responsibilities

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.

Benefits

Competitive salary
Meaningful equity
Health insurance benefits: medical (various PPO/HMO/HSA plans), dental, vision, disability and life insurance
401k plan
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