Staff ML Engineer: Scale Recommendations & LLMs

Grindr; Palo Alto, San Francisco (CA, CA); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health, Dental & Vision

Family Formation

Retirement: 401(k) with match

Compensation & equity

Gender-affirming care

Time Off & Rest

Other benefits: stipends

Job summary

Grindr, an AI-native platform for global LGBTQ+ connections, is seeking an experienced ML engineer to architect scalable recommendation systems and leverage cutting-edge LLMs across huge user data. You will collaborate with engineering, data science, and product teams to ship production-ready ML solutions that drive real user impact.

The role requires 7+ years of ML system development, fluency in Python, and experience with cloud platforms (AWS, GCP or Databricks).

Qualifications

• 7+ years of experience building ML systems from scratch.
• Fluency in Python and popular ML frameworks.
• Experience with data deployment technologies and cloud environments such as AWS, GCP or Databricks.
• Experience with recommendation systems or similar is a plus.

Responsibilities

• Architect scalable recommendation systems to serve millions, balancing performance and innovation.
• Leverage the latest LLMs to process vast conversation data and enhance user connections.
• Prototype, iterate, and ship production-ready ML solutions that solve real problems for our user.
• Collaborate cross-functionally with engineering, data science and product teams to turn bold ideas into tangible results.
• Drive the exploration of emerging AI tools and techniques to keep Grindr’s tech stack ahead of the curve.

Skills

Python

ML frameworks

Scrappy mindset

LLM workflows

Cross-functional collaboration

Tools

Snowflake

Airflow

Kubernetes

Docker

Helm

Spark

PySpark

Job description

Grindr, an AI-native platform for global LGBTQ+ connections, is seeking an experienced ML engineer to architect scalable recommendation systems and leverage cutting-edge LLMs across huge user data. You will collaborate with engineering, data science, and product teams to ship production-ready ML solutions that drive real user impact.

The role requires 7+ years of ML system development, fluency in Python, and experience with cloud platforms (AWS, GCP or Databricks).