Machine Learning Engineer, Marker Learning
Learning disability support
Job no longer available
Learning disability support
21-100 employees
Job no longer available
21-100 employees
Company mission
To democratize access to high quality learning assessments and services.
Role
Who you are
- B.S, Masters or PhD in Computer Science, Mathematics, Statistics, or a related field4+ years of experience in developing and deploying machine learning models in a production environment
- Strong understanding of machine learning algorithms, deep learning, and natural language processing
- Proficiency in Python
- Excellent communication skills with both technical and non-technical stakeholders
Desirable
- Experience with computer vision frameworks (e.g., OpenCV, TensorFlow), audio processing libraries (e.g., librosa, pydub), and NLP libraries (e.g., spaCy, NLTK, Hugging Face Transformers)
- Knowledge of advanced NLP techniques such as transformer-based models, language model fine-tuning, or dynamic few-shot learning
What the job involves
- As a Machine Learning Engineer at Marker, you will contribute to the development of innovative AI-based tools that aim to improve the process of learning disability evaluations
- You will collaborate closely with our team of data scientists, clinicians, and psychologists to design, implement, and deploy machine learning models that leverage the latest advancements in AI and psychometric science
- Your work will contribute to making learning disability evaluations more accessible, standardized, and with repeatable outcomes, while ensuring scientifically valid and reliable solutions for our students, schools, psychologists, and internal stakeholders
- Be one of the first Machine Learning Engineers at an early-stage project, with leadership opportunities and project diversity
- Design, implement, and deploy machine learning models for assessment tools and methodologies
- Collaborate with data scientists and psychometricians to integrate machine learning techniques into psychometric test development
- Work with one of the largest learning differences datasets to develop models for in-depth analysis of assessment results and ensure high clinical quality standards
- Deploy and integrate large language models (LLMs) and other natural language processing (NLP) solutions into production environments, ensuring high performance, scalability, and reliability while collaborating with software engineers to streamline the deployment process and monitor model performance in real-world applications
- Stay up-to-date with the latest research and best practices in machine learning and AI, ensuring our assessment tools remain at the forefront of the field
- Communicate findings and insights to both technical and non-technical stakeholders, including product managers, designers, and clinicians
Our take
One in five American students has a learning disability, and while a proper evaluation could be one of the most impactful events in these students' lives, only 4% receive a diagnosis because of the high costs involved and the lack of access to the appropriate psychologists. Undiagnosed students are more likely to drop out of school, fail to find a job and subsequently suffer from mental health issues.
The current learning disability support system is broken, and Marker Learning is setting out to change this by making critical learning disability evaluations and support more accessible and affordable. The startup is leveraging technology developed by experts at John Hopkins to provide evaluations in half the time and at a fraction of the price.
Having already reached a million students through school partnerships, Marker Learning is rapidly growing and raised $15 million in 2023. It announced its expansion into multiple new services as well, including tutoring and coaching. The startup is backed by some of the most mission-driven venture capital firms in the industry and with their help, it plans to continue scaling its partnerships and expand into new geographies.
Freddie
Company Specialist at Welcome to the Jungle
Insights
220% employee growth in 12 months
Company
Funding (2 rounds)
Feb 2023
$15m
SERIES A
Nov 2021
$4.7m
SEED
Total funding: $19.7m
Company HQ
Civic Center, New York, NY
Leadership
Stefan Bauer
(Co-Founder & CEO)Previously worked as an Analyst at Bloomberg and Morgan Stanley, also worked as an Associate and Engagement Manager at McKinsey & Company.
Emily Yudofsky
(Co-Founder & Chief Product & Marketing Officer)Previously founded the company Found, a pioneering weight care platform where they served as CEO. Also worked at Google as a Product Marketing Manager.
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