Description:

The Applied Science team at Gretel is seeking a Machine Learning Engineer who is passionate about building software that developers love.
Gretel is focused on creating a platform that combines differential privacy with AI to generate synthetic data, enabling organizations to unlock sensitive data for AI development and analytics.
The company promotes a collaborative remote-first culture with employees across the U.S. and Canada, offering autonomy and trust to its team members.
The ideal candidate will thrive in a fast-paced startup environment and enjoy working cross-functionally to solve complex problems.
Responsibilities include designing and implementing software for core products, collaborating with applied scientists, engineers, and product managers, and unlocking real-world use cases for synthetic data generation.

Requirements:

Candidates must have 5+ years of professional experience in software development, ideally with a specialization in machine learning.
Significant experience with tools from Python’s machine learning ecosystem is required.
A strong foundation in deep learning and related mathematics is necessary.
Demonstrated experience working on complex software projects with a track record of delivering technical excellence is essential.
Nice to have: Experience working remotely in a distributed company, developing large-scale models, and deploying them into production, as well as experience with LLM evaluations and information-retrieval systems.

Compensation will be determined based on interview performance, experience, specialization, and market rate, with salary ranges for Senior Machine Learning Engineer between $180,000-$210,000 USD and for Staff Machine Learning Engineer between $200,000-$230,000 USD.
Employees can expect a comprehensive benefits package, including bonuses for applicable roles and stock options.
Gretel is committed to creating an inclusive environment and offers accommodations for candidates with disabilities.
The company values diversity and aims to blend various perspectives and experiences to foster innovation and collaboration.