Senior Machine Learning Engineer

Kiddom • Full-time • Hybrid in New York, New York, United States • $175,000 - $250,000 / year • 1m ago

Fast Facts

We are seeking a Senior Machine Learning Engineer to join Kiddom's AI team in New York, where you'll design and scale machine learning systems to enhance educational experiences through personalized content and intelligent insights.

Responsibilities: You will architect ML systems for search and recommendations, develop evaluation workflows for teaching efficiency, fine-tune models using feedback, create intelligent discovery pipelines, and mentor junior engineers.

Skills: Required skills include 5+ years in machine learning, strong programming in Python, expertise in ML toolkits, and excellent analytical and communication abilities.

Qualifications: Preferred qualifications include deep learning framework expertise, experience with ML evaluation pipelines, and familiarity with large language models and foundation model adaptation techniques.

Location: The job is located in New York, USA.

Compensation: $175000 - $250000 / Annually

About Kiddom

Kiddom is a groundbreaking educational platform that promotes student equity and growth by uniting high-quality instructional materials with dynamic digital learning. Through unparalleled curriculum management functionality, Kiddom empowers schools and districts to take ownership of their curriculum – resulting in learning experiences tailored to meet the unique needs and goals of local communities. Kiddom’s high-quality curriculum is layered with robust teacher and leader data insights to drive the continuous improvement of instructional decisions, school/district programming, and professional learning.

What the job involves

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.

What the job involves

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.

Who you are

Have 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.

Desirable

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.

$175,000 - $250,000 a year

Salary range is dependent on geographic location, prior experience, seniority, and demonstrated role related ability during the interview process.

What we offer

Full time permanent employees are eligible for the following benefits from their first day of employment:

* 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

Equal Employment Opportunity Policy

Kiddom is committed to providing equal employment opportunities to all employees and applicants without regard to race, religion, color, gender, sexual orientation, transgender status, national origin, citizenship status, uniform service member status, pregnancy, age, genetic information, disability, or any other protected status in accordance with all applicable federal, state, and local laws.