Senior Machine Learning Engineer

Child Mind Institute•New York, NY

43d•$118,000 - $148,000•Hybrid

About The Position

As the Senior Machine Learning (ML) Engineer, you will apply expertise in Natural Language Processing (NLP) and Large Language Models (LLMs) to develop and implement innovative ML solutions that have the potential to make a significant impact in the lives of children and adolescents struggling with mental health issues. You will work with researchers, clinicians, and software engineers within DAIR and across departments to design, prototype, deploy and maintain applied ML solutions to enhance our digital mental health tools. This is an exempt, full-time, hybrid position located in our NYC headquarters office. The in-office requirement and schedule are subject to change based on the needs of the program and the organization. This position requires a minimum of four (4) days per week in the office, on a schedule determined by your supervisor.

Requirements

Master's degree in Neuroscience, Psychology, Engineering, Computer Science or equivalent combination of education and experience.
8+ years of experience in data analysis and data science fundamentals (e.g., algorithms, data structures, data visualization, machine learning).
8+ years of experience in at least one scientific programming language (e.g., Python/R, Matlab) and related toolboxes or frameworks (e.g., Tidyverse, Scipy, Sklearn, Polars, Pytorch) is required.
5+ years of experience working in a Linux environment, using version control systems (e.g., GitHub), and software virtualization platforms (e.g., Docker).
3+ years of practical experience developing and designing production-oriented machine learning technologies and systems, including hands-on experience in NLP and modern ML/NLP.toolchains (e.g., pytorch, tensorflow, SpaCy, HuggingFace, NLTK).
Experience can be concurrent with education.

Responsibilities

Design, implement, and maintain machine learning models with a focus on NLP and LLMs for real-world application in the mental health field.
Perform analyses on large datasets using high-performance computing infrastructures.
Collaborate with cross-functional teams to integrate ML solutions into research projects and mental health tools.
Develop and maintain data pipelines for training, evaluating, and deploying models.
Leverage expertise to create innovative solutions to complex problems using state-of-the-art ML methods.
Ensure data quality, security, and compliance with privacy regulations.
Perform additional job-related duties as assigned.