Staff Machine Learning Engineer

Role Overview

Join Grindr as a Staff Machine Learning Engineer to build scalable recommendation systems and LLM-powered solutions. You’ll work cross-functionally with engineering, data science, and product teams to prototype, productionize, and continuously improve ML capabilities.

Key Missions

• Architect scalable recommendation systems that can serve millions of users while balancing performance and innovation.
• Prototype, iterate, and ship production-ready ML solutions that address real user problems.
• Collaborate cross-functionally to turn bold ideas into tangible results.
• Explore emerging AI tools and techniques to keep Grindr’s AI stack ahead.

Requirements

• 7+ years building ML systems, with strong 0-to-1 capability development from scratch.
• Experience with recommendation systems (or similar) is a plus.
• Experience with a public cloud environment: AWS, GCP, or Databricks.
• Hands-on experience building machine/deep learning models using frameworks such as PyTorch, TensorFlow, or Keras.
• Demonstrated ability to deliver at scale, with fluency in Python and common ML frameworks.
• Scrappy mindset to tackle messy problems and produce real outcomes.
• Experience with data/deployment technologies such as Snowflake, Airflow, Kubernetes, Docker, Helm, Spark, PySpark.
• Expertise in LLM workflows for nuanced, human-driven tasks.
• Proven record of recommendation systems that perform well across diverse user needs.
• Thrives in a fast-paced, outcome-driven environment with heavy cross-functional collaboration.
• Track record of product ownership, addressing the needs of specific user groups from early-stage concept through full rollout.

Nice-to-haves

• Prior experience specifically in recommendation systems (if not already core).