Major Responsibilities:- Define and drive machine learning strategy across multiple domains and product areas while actively contributing to implementation
- Design, build, and scale production ML systems, pipelines, and services
- Establish standards for model architecture, evaluation, deployment, and lifecycle management
- Lead development of complex ML solutions, partnering with Data Scientists to bring models into production
- Leverage agentic AI to speed up development and deliver features on a consistent cadence
- Drive enterprise MLOps strategy, including deployment, monitoring, and model governance
- Define and implement scalable feature engineering and data pipeline strategies
- Lead cross-functional initiatives to improve ML system performance, reliability, and scalability
- Solve highly complex, ambiguous technical problems through hands-on development and technical leadership
- Mentor senior engineers and influence technical direction across teams
- Evaluate and adopt new tools, technologies, and best practices to advance ML capabilities
Skills & Qualifications:- 10+ years of experience building and deploying machine learning systems at scale
- Proven track record of leading and delivering large, complex ML initiatives
- Strong expertise in ML frameworks (e.g., TensorFlow, PyTorch, XGBoost) and distributed systems
- Extensive programming experience in Python required, Golang experience preferred
- Experience in building data pipelines in cloud environment such as airflow
- Experience in developing multi-agent systems and RAG architectures
- Experience with cloud platforms (AWS, GCP, Azure) and big data ecosystems
- Deep understanding of MLOps and production ML systems
- Experience working with AI governance guidelines and compliance requirements in the industry
- Strong software engineering and system design skills
- Ability to balance strategic thinking with hands-on execution
- Excellent communication and stakeholder management skills.
Engineering teams are responsible for supporting appropriate security controls, including management, operational, and technical controls in addition to general GoodRx best practices, such as reading and adhering to the security policies and procedures, being vigilant and observant of potential security threats, etc.
At GoodRx, pay ranges are determined based on work locations and may vary based on where the successful candidate is hired. The pay ranges below are shown as a guideline, and the successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, and other relevant business and organizational factors. These pay zones may be modified in the future. Please contact your recruiter for additional information.
San Francisco and Seattle Offices:
$253,000.00 - $404,000.00
New York Office:
$232,000.00 - $371,000.00
Santa Monica Office:
$211,000.00 - $337,000.00
Other Office Locations:
$190,000.00 - $303,000.00
GoodRx also offers additional compensation programs such as annual cash bonuses or commission, and annual equity grants for most positions as well as generous benefits. Our great benefits offerings include medical, dental, and vision insurance, 401(k) with a company match, an ESPP, unlimited vacation, 13 paid holidays, and 72 hours of sick leave. GoodRx also offers additional benefits like mental wellness and financial wellness programs, fertility benefits, generous parental leave, pet insurance, supplemental life insurance for you and your dependents, company-paid short-term and long-term disability, and more!
