Senior Machine Learning Engineer

Child Mind Institute; New York (NY); Hybrid; USD 120,000 - 160,000; Full time

Benefits offered by this job

Medical insurance

401(k)

Paid parental leave

Discounted tickets and entertainment perks

Job summary

The Child Mind Institute is seeking a Senior Machine Learning Engineer to enhance digital mental health tools using NLP and ML solutions. This role includes collaboration with researchers and clinicians to develop and maintain models, ensuring data quality and compliance.

Applicants should have a Master’s degree and extensive experience in data science, programming languages, and ML tools. Benefits include medical insurance, 401(k), and paid parental leave.

Qualifications

• Master's degree in a relevant field.
• 8+ years of experience in data analysis and data science.
• 8+ years in scientific programming languages.

Responsibilities

• Develop and implement ML solutions for mental health.
• Analyze large datasets using high-performance computing.
• Collaborate with cross-functional teams to integrate ML solutions.

Skills

Natural Language Processing (NLP)

Machine Learning (ML)

Data Analysis

Python/R

Linux

TensorFlow

Docker

Education

Master's degree in Neuroscience, Psychology, Engineering, or Computer Science

Tools

GitHub

Pytorch

Job description

Position Details

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 collaborate 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.

You Will

• 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.

You Have

• 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.

Our Benefits

Our great compensation package and benefits include medical insurance, 401(k), paid parental leave, dependent care, discounted tickets and entertainment perks programs. For more information about our benefits, please visit our employee benefits website.

Pay Range

The salary range for the position is posted. Factors such as candidate's work experience, education/training, job‑related skills, internal peer equity, as well as market and business considerations affect the salary offered within this range. In addition, this salary may be subject to a geographic adjustment (according to a specific city and state and depending on the role), if an authorization is granted to work outside of the location listed in this posting.

EEO Disclaimer

Child Mind Institute is committed to fostering an inclusive and equitable workplace where all individuals are treated with respect and dignity. We are proud to be an equal opportunity employer and prohibit discrimination and harassment of any kind.

We provide equal employment opportunities to all employees and applicants for employment, regardless of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), sexual orientation, gender identity, gender expression, age, national origin, ancestry, citizenship status, marital status, military or veteran status, physical or mental disability, genetic information, medical condition, or any other characteristic protected by applicable federal, state, or local laws.

In compliance with California law, we also prohibit discrimination based on reproductive health decision‑making, status as a victim of domestic violence, sexual assault, or stalking, or any other category protected by the California Fair Employment and Housing Act (FEHA). In New York, we extend this prohibition to include status as a victim of domestic violence, familial status, or any other characteristic protected by the New York State Human Rights Law (NYSHRL).

Child Mind Institute is dedicated to ensuring accessibility and reasonable accommodations for individuals with disabilities or medical conditions. If you require an accommodation to participate in the application process or perform your job, please contact our HR Department at [e-mail].

This policy applies to all aspects of employment, including recruitment, hiring, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, benefits, and training.