TL;DR

Senior Machine Learning Scientist (AI Engineering): Developing and optimizing advanced machine learning models and language models integrated into global education products with an accent on model training, dataset construction, and production readiness. Focus on designing novel architectures, fine-tuning LLMs, and scaling ML systems for worldwide impact.

Location: Remote (USA only)

Salary: $111,000–$185,000 per year

Company

%hirify_global% is a global leader in education technology, providing integrity and assessment solutions to over 21,000 academic institutions worldwide with a remote-first culture.

What you will do

Collaborate with subject matter experts and product owners to define key ML questions and curate datasets.
Develop, tune, and optimize machine learning and deep learning models, including language models and LLMs.
Maintain and harden models for production pipelines ensuring scalability and reliability.
Stay current with research, experiment with new architectures, and share insights across teams.
Write clean, modular code with automated tests and documentation.
Communicate model behavior, limitations, and insights effectively to stakeholders.

Requirements

Must have at least 8 years of software engineering experience with Python, SQL, and Unix-based systems.
Strong background in machine learning, deep learning, and language models including training and fine-tuning LLMs.
Master's or PhD in Computer Science, Electrical Engineering, AI, or related field with relevant industry experience.
Fluent in written and spoken English.
Experience with ML experiment tracking tools and cloud platforms like AWS SageMaker.
Excellent communication and teamwork skills.

Nice to have

Experience coding for production environments and building backend API services.
DevOps skills including Docker and AWS EC2/Batch/Lambda.
Frontend development experience for demos or prototypes using React, JavaScript, or Flask.
Experience with advanced prompting and fine-tuning of LLMs on platforms like mosaic.ai or stochastic.ai.
Portfolio showcasing previous work such as open source projects or presentations.

Culture & Benefits

Remote-first culture with flexible work arrangements.
Comprehensive health care coverage and wellness programs.
Competitive paid time off including self-care days and national holidays.
Education reimbursement and professional development support.
Parental leave and retirement plans with matching contributions.
Inclusive, collaborative, and globally diverse team environment.